Referências

ABBOTT, B. Presuppositions and common ground. Linguistics and philosophy, v. 31, p. 523–538, 2008.

ABERCROMBIE, G. et al. Mirages. On Anthropomorphism in Dialogue Systems. (H. Bouamor, J. Pino, K. Bali, Eds.)Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Anais...Singapore: Association for Computational Linguistics, dez. 2023. Disponível em: <https://aclanthology.org/2023.emnlp-main.290>

ABNEY, S. P. Parsing By Chunks. Em: BERWICK, R. C.; ABNEY, S. P.; TENNY, C. (Eds.). Principle-Based Parsing: Computation and Psycholinguistics. Dordrecht: Springer Netherlands, 1992. p. 257–278.

ACHIAM, J. et al. Gpt-4 technical report. arXiv preprint arXiv:2303.08774, 2023.

ACOSTA, O.; VILLAVICENCIO, A.; MOREIRA, V. Identification and Treatment of Multiword Expressions Applied to Information Retrieval. Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World. Anais...Portland, Oregon, USA: Association for Computational Linguistics, jun. 2011. Disponível em: <https://aclanthology.org/W11-0815>

AFANTENOS, S.; ASHER, N. Counter-argumentation and discourse: A case study. Proceedings of the Workshop on Frontiers and Connections between Argumentation Theory and Natural Language Processing. Anais...CEUR Workshop Proceedings, 2014.

AFONSO, S. et al. Floresta sintá(c)tica: a treebank for Portuguese. (M. G. Rodrigues, C. P. S. Araujo, Eds.)Proceedings of the Third International Conference on Language Resources and Evaluation (LREC 2002). Anais...Paris: ELRA, 2002.

AHN, L. VON; KEDIA, M.; BLUM, M. Verbosity: A Game for Collecting Common-Sense Facts. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Anais...: CHI ’06.New York, NY, USA: Association for Computing Machinery, 2006. Disponível em: <https://doi.org/10.1145/1124772.1124784>

AI and Ethics. Springer, 2023. Disponível em: <https://link.springer.com/journal/43681/volumes-and-issues>. Acesso em: 7 abr. 2023

AKÇAY, M. B.; OĞUZ, K. Speech emotion recognition: Emotional models, databases, features, preprocessing methods, supporting modalities, and classifiers. Speech Communication, v. 116, p. 56–76, 2020.

ALAM, T.; KHAN, A.; ALAM, F. Punctuation Restoration using Transformer Models for High-and Low-Resource Languages. Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020). Anais...Online: Association for Computational Linguistics, nov. 2020. Disponível em: <https://aclanthology.org/2020.wnut-1.18>

ALCAIM, A.; SOLEWICZ, J. A.; MORAES, J. A. DE. Freqüência de ocorrência dos fones e listas de frases foneticamente balanceadas no português falado no Rio de Janeiro. Journal of Communication and Information Systems, v. 7, n. 1, 1992.

ALEIXO, P.; PARDO, T. A. S. CSTTool: um parser multidocumento automático para o Português do Brasil. IV Workshop on MSc Dissertation and PhD Thesis in Artificial Intelligence–WTDIA. Anais...b2008.

ALEIXO, P.; PARDO, T. A. S. CSTNews: um córpus de textos jornalísticos anotados segundo a teoria discursiva multidocumento CST (Cross-document Structure Theory. [s.l.] Universidade de São Paulo (USP); São Carlos, SP, Brasil., a2008. Disponível em: <http://repositorio.icmc.usp.br//handle/RIICMC/6761>.

ALENCAR, L. F. DE. Donatus: uma interface amigável para o estudo da sintaxe formal utilizando a biblioteca em Python do NLTK. Alfa: Revista de Linguística (São José do Rio Preto), v. 56, n. 2, p. 523–555, jul. 2012.

ALENCAR, L. F. DE; CUCONATO, B.; RADEMAKER, A. MorphoBr: an open source large-coverage full-form lexicon for morphological analysis of Portuguese. Texto Livre, v. 11, n. 3, p. 1–25, dez. 2018.

ALENCAR, R. Processos de categorização social: emergência de categorias sociais na fala em interação. Revista Investigações, v. 21, n. 2, p. 115–131, 2008.

ALENCAR, V.; ALCAIM, A. LSF and LPC-derived features for large vocabulary distributed continuous speech recognition in Brazilian Portuguese. 2008 42nd Asilomar Conference on Signals, Systems and Computers. Anais...IEEE, 2008.

ALISSON, S. Their god is not our god. Disponível em: <https://www.thecontinent.org/_files/ugd/287178_73f3d2af22614e678f277b631a62e491.pdf>. Acesso em: 11 jun. 2023.

ALLWOOD, J.; TRAUM, D.; JOKINEN, K. Cooperation, dialogue and ethics. International Journal of Human-Computer Studies, v. 53, n. 6, p. 871–914, 2000.

ALMASI, M.; SCHIØNNING, A. Fine-Tuning GPT-3 for Synthetic Danish News Generation. Proceedings of the 16th International Natural Language Generation Conference. Anais...2023.

ALTMANN, G. T.; KAMIDE, Y. Incremental interpretation at verbs: Restricting the domain of subsequent reference. Cognition, v. 73, n. 3, p. 247–264, 1999.

ALTMANN, G. T.; MIRKOVIĆ, J. Incrementality and prediction in human sentence processing. Cognitive science, v. 33, n. 4, p. 583–609, 2009.

ALTUNYURT, L.; ORHAN, Z.; GÜNGÖR, T. A Composite Approach for Part of Speech Tagging in Turkish. 2006. Disponível em: <https://api.semanticscholar.org/CorpusID:9439761>

ALUÍSIO, S. et al. An Account of the Challenge of Tagging a Reference Corpus for Brazilian Portuguese. (N. J. Mamede et al., Eds.)Computational Processing of the Portuguese Language. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2003.

ALZUBAIDI, L. et al. A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications. Journal of Big Data, v. 10, abr. 2023.

AMARAL, C. et al. Priberam’s question answering system in qa@ clef 2008. Workshop of the Cross-Language Evaluation Forum for European Languages. Anais...Springer, 2008.

AMARAL, D. O. F. DO. O reconhecimento de entidades nomeadas por meio de conditional random fields para a lı́ngua portuguesa. Dissertação de Mestrado, Pontifı́cia Universidade Católica do Rio Grande do Sul, 2013.

ANACLETO, J. et al. Can Common Sense uncover cultural differences in computer applications? (M. Bramer, Ed.)Artificial Intelligence in Theory and Practice. Anais...Boston, MA: Springer US, 2006.

ANACLETO, J. C. et al. A Common Sense-Based On-Line Assistant for Training Employees. (C. Baranauskas et al., Eds.)Human-Computer Interaction – INTERACT 2007. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2007.

ANANTHAKRISHNAN, S.; NARAYANAN, S. S. Automatic Prosodic Event Detection Using Acoustic, Lexical, and Syntactic Evidence. IEEE Transactions on Audio, Speech, and Language Processing, v. 16, n. 1, p. 216–228, 2008.

ANDROUTSOPOULOS, I.; LAMPOURAS, G.; GALANIS, D. Generating Natural Language Descriptions from OWL Ontologies: The Natural OWL System. Journal of Artificial Intelligence Research, v. 48, n. 1, p. 671–715, out. 2013.

ANTONIO, J. D. Proposições relacionais e conversação: uma análise das relações estabelecidas nas trocas de turno. Acta Scientiarum: Human and social sciences, v. 25, p. 59, 2003.

ANTUNES, I. Lutar com palavras: coesão e coerência. [s.l.] Parábola, 2007.

ANTUNES, I. Textualidade: noções básicas e implicações pedagógicas. [s.l.] Editora: Parábola Editorial, 2017.

APPELT, D. E. Problem Solving Applied to Language Generation. Proceedings of the 18th Annual Meeting on Association for Computational Linguistics. Anais...: ACL’80.Philadelphia, Pennsylvania: Association for Computational Linguistics, 1980. Disponível em: <https://doi.org/10.3115/981436.981455>

ARDILA, R. et al. Common voice: A massively-multilingual speech corpus. arXiv preprint arXiv:1912.06670, 2019.

Artificial intelligence and human rights. 1. ed. [s.l.] Dykinson, S.L., 2021.

ASHER, N. et al. Discourse structure and dialogue acts in multiparty dialogue: the STAC corpus. 10th International Conference on Language Resources and Evaluation (LREC 2016). Anais...2016.

ASHER, N.; LASCARIDES, A. Logics of conversation. [s.l.] Cambridge University Press, 2003.

ASHER, N.; VIEU, L. Subordinating and coordinating discourse relations. Lingua, v. 115, n. 4, p. 591–610, 2005.

AUER, S. et al. DBpedia: A Nucleus for a Web of Open Data. (K. Aberer et al., Eds.)The Semantic Web. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2007.

AVELAR, M.; FERRARI, L. Integração experiencial e dêixis locativa: O papel discursivo dos gestos. Cadernos de Estudos Linguı́sticos, v. 59, n. 1, p. 73–89, 2017.

AZEVEDO, R. R. DE. Um sistema de diálogo inteligente baseado em lógica de descrições. tese de doutorado—[s.l.] Universidade Federal de Pernambuco, 2015.

BAADER, F. et al. The Description Logic Handbook: Theory, Implementation and Applications. Cambridge, Reino Unido: Cambridge University Press, 2003.

BÄCKSTRÖM, T. et al. Introduction to Speech Processing. 2. ed. [s.l: s.n.].

BADENE, S. et al. Learning Multi-party Discourse Structure Using Weak Supervision. 25th International conference on computational linguistics and intellectual technologies (Dialogue 2019). Anais...2019.

BAEVSKI, A. et al. wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations., 2020. Disponível em: <https://arxiv.org/abs/2006.11477>

BAGGA, A.; BALDWIN, B. Algorithms for Scoring Coreference Chains. Proceedings of the first International Conference on Language Resources and Evaluation Workshop on Linguistics Coreference. Anais...Granada, Spain: 1998.

BAHDANAU, D.; CHO, K.; BENGIO, Y. Neural Machine Translation by Jointly Learning to Align and Translate. (Y. Bengio, Y. LeCun, Eds.)3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings. Anais...San Diego, California.: 2015. Disponível em: <http://arxiv.org/abs/1409.0473>

BAKER, C. F.; FILLMORE, C. J.; LOWE, J. B. The Berkeley FrameNet Project. 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, Volume 1. Anais...Montreal, Quebec, Canada: Association for Computational Linguistics, ago. 1998. Disponível em: <https://aclanthology.org/P98-1013>

BAKER, C.; FELLBAUM, C.; PASSONNEAU, R. Semantic Annotation of MASC. Em: Handbook of Linguistic Annotation. [s.l.] Springer Netherlands, 2017. p. 699–717.

BALDWIN, T.; KIM, S. N. Multiword Expressions. Em: INDURKHYA, N.; DAMERAU, F. J. (Eds.). Handbook of Natural Language Processing. 2. ed. Boca Raton, FL, USA: CRC Press, Taylor; Francis Group, 2010. p. 267–292.

BALLOCCU, S. et al. Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs. (Y. Graham, M. Purver, Eds.)Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers). Anais...St. Julian’s, Malta: Association for Computational Linguistics, mar. 2024. Disponível em: <https://aclanthology.org/2024.eacl-long.5/>

BANARESCU, L. et al. Abstract Meaning Representation for Sembanking. Proceedings of the 7th Linguistic Annotation Workshop and Interoperability with Discourse. Anais...Sofia, Bulgaria: Association for Computational Linguistics, 2013. Disponível em: <http://aclweb.org/anthology/W13-2322>

BANERJEE, S.; LAVIE, A. METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments. (J. Goldstein et al., Eds.)Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization. Anais...Ann Arbor, Michigan: Association for Computational Linguistics, jun. 2005. Disponível em: <https://aclanthology.org/W05-0909>

BANSAL, N.; AGARWAL, C.; NGUYEN, A. SAM: The Sensitivity of Attribution Methods to Hyperparameters. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Anais...2020. Disponível em: <https://doi.org/10.1109/CVPRW50498.2020.00009>

BAPTISTA, J.; HAGÈGE, C.; MAMEDE, N. Identificação, classificação e normalização de expressões temporais do português: A experiência do Segundo HAREM e o futuro. Em: MOTA, C.; SANTOS, D. (Eds.). Desafios na avaliação conjunta do reconhecimento de entidades mencionadas. [s.l.] Linguateca, 2008. p. 33–54.

BAPTISTA, J.; MAMEDE, N.; REIS, S. Support Verb Constructions across the Ocean Sea. (A. Bhatia et al., Eds.)Proceedings of the 18th Workshop on Multiword Expressions @LREC2022. Anais...Marseille, France: European Language Resources Association, jun. 2022. Disponível em: <https://aclanthology.org/2022.mwe-1.6>

BARREIRA, R.; PINHEIRO, V.; FURTADO, V. FrameFOR – Uma Base de Conhecimento de Frames Semânticos para Perı́cias de Informática (FrameFOR - a Knowledge Base of Semantic Frames for Digital Forensics)[In Portuguese]. Proceedings of the 11th Brazilian Symposium in Information and Human Language Technology. Anais...Uberlândia, Brazil: Sociedade Brasileira de Computação, out. 2017. Disponível em: <https://aclanthology.org/W17-6620>

BARREIRO, A. et al. When Multiwords Go Bad in Machine Translation. MT Summit workshop Proceedings on Multi-word Units in Machine Translation and Transla tion Technology, p. 10, 2013.

BARROS, D. L. P. DE. Procedimentos e recursos discursivos da conversação. Estudos de lı́ngua falada: variações e confrontos, v. 3, p. 47, 1999.

BARROS, D. L. P. DE. Introdução à Linguística II: princípios de análise. Em: FIORIN, J. L. (Ed.). 5. ed. São Paulo: Contexto, 2021. p. 187–219.

BARZILAY, R.; LAPATA, M. Collective Content Selection for Concept-to-text Generation. Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing. Anais...: HLT’05.Vancouver, British Columbia, Canada: Association for Computational Linguistics, 2005. Disponível em: <https://doi.org/10.3115/1220575.1220617>

BARZILAY, R.; LAPATA, M. Aggregation via Set Partitioning for Natural Language Generation. Proceedings of the Main Conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics. Anais...: HLT-NAACL’06.New York, New York: Association for Computational Linguistics, 2006. Disponível em: <https://doi.org/10.3115/1220835.1220881>

BASILE, V. et al. It’s the end of the gold standard as we know it. On the impact of pre-aggregation on the evaluation of highly subjective tasks. CEUR Workshop Proceedings. Anais...CEUR-WS, 2020. Disponível em: <https://iris.unito.it/handle/2318/1770149>

BASILE, V. et al. We Need to Consider Disagreement in Evaluation. Proceedings of the 1st Workshop on Benchmarking: Past, Present and Future. Anais...Online: Association for Computational Linguistics, ago. 2021. Disponível em: <https://aclanthology.org/2021.bppf-1.3>

BASSO, R. M. A Semântica das Relações Anafóricas entre Eventos. tese de doutorado—[s.l.] Universidade Estadual de Campinas, SP, 2009.

BATES, M. et al. Research in Knowledge Representation for Natural Language Understanding: Bolt, Beranek, and Newman. SIGART Bull., n. 79, p. 30–31, jan. 1982.

BATISTA, C.; DIAS, A. L.; NETO, N. Free resources for forced phonetic alignment in Brazilian Portuguese based on Kaldi toolkit. EURASIP Journal on Advances in Signal Processing, v. 2022, n. 1, p. 11, 19 fev. 2022.

BAVELAS, J. B. et al. Interactive gestures. Discourse Processes, v. 15, n. 4, p. 469–489, 1992.

BAVELAS, J. B. Face-to-face dialogue: theory, research, and applications. [s.l.] Oxford University Press, 2022.

BAVELAS, J. B.; COATES, L.; JOHNSON, T. Listener responses as a collaborative process: The role of gaze. Journal of communication, v. 52, n. 3, p. 566–580, 2002.

BAVELAS, J. B.; GERWING, J. Conversational hand gestures and facial displays in face-to-face dialogue. Em: Social communication. [s.l.] Psychology Press, 2007. p. 283–308.

BAYYARAPU, H. S. Efficient algorithm for Context Sensitive Aggregation in Natural Language generation. Proceedings of the International Conference Recent Advances in Natural Language Processing. Anais...: RANLP’11.Hissar, Bulgaria: Association for Computational Linguistics, 2011. Disponível em: <http://aclanthology.coli.uni-saarland.de/pdf/R/R11/R11-1012.pdf>

BEATTIE, G. W. Sequential Temporal Patterns of Speech and Gaze in Dialogue. Semiotica, v. 23, n. 1/2, 1978.

BECKMAN, M. E.; HIRSCHBERG, J.; SHATTUCK-HUFNAGEL, S. The original ToBI system and the evolution of the ToBI framework. Em: JUN, S.-A. (Ed.). Prosodic typology: the phonology of intonation and phrasing. Oxford: Oxford University Press, 2005. p. 9–54.

BEJČEK, E.; STRAŇÁK, P.; PECINA, P. Syntactic Identification of Occurrences of Multiword Expressions in Text using a Lexicon with Dependency Structures. Proceedings of the 9th Workshop on Multiword Expressions. Anais...Atlanta, Georgia, USA: Association for Computational Linguistics, jun. 2013. Disponível em: <https://aclanthology.org/W13-1016>

BELHASIN, O.; BAR-SHALOM, G.; EL-YANIV, R. TransBoost: improving the best ImageNet performance using deep transduction. Proceedings of the 36th International Conference on Neural Information Processing Systems. Anais...: NIPS ’22.Red Hook, NY, USA: Curran Associates Inc., 2022.

BELINKOV, Y.; GLASS, J. Analysis Methods in Neural Language Processing: A Survey. Transactions of the Association for Computational Linguistics, v. 7, p. 49–72, 2019.

BELZ, A. Last Words: That’s Nice ... What Can You Do With It? Computational Linguistics, v. 35, n. 1, mar. 2009.

BELZ, A. et al. A Systematic Review of Reproducibility Research in Natural Language Processing. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Anais...Online: Association for Computational Linguistics, abr. 2021. Disponível em: <https://aclanthology.org/2021.eacl-main.29>

BELZ, A. A Metrological Perspective on Reproducibility in NLP*. Computational Linguistics, v. 48, n. 4, p. 1125–1135, dez. 2022.

BELZ, A. et al. Non-Repeatable Experiments and Non-Reproducible Results: The Reproducibility Crisis in Human Evaluation in NLP. Findings of the Association for Computational Linguistics: ACL 2023. Anais...Toronto, Canada: Association for Computational Linguistics, jul. a2023. Disponível em: <https://aclanthology.org/2023.findings-acl.226>

BELZ, A.; THOMSON, C.; REITER, E. Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP. The Fourth Workshop on Insights from Negative Results in NLP. Anais...Dubrovnik, Croatia: Association for Computational Linguistics, b2023. Disponível em: <https://aclanthology.org/2023.insights-1.1>

BENDER, E. M. Linguistic Fundamentals for Natural Language Processing: 100 Essentials from Morphology and Syntax. Springer Nature Switzerland AG 2013: Springer Cham, 2013. p. XVII–166

BENDER, E. M. The Power of Linguistics - Unpacking Natural Language Processing Ethics with Emily M. Bender. [Podcast]. Disponível em: <https://www.radicalai.org/e16-emily-bender>. Acesso em: 7 abr. 2023.

BENDER, E. M. et al. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency. Anais...: FAccT ’21.New York, NY, USA: Association for Computing Machinery, 2021. Disponível em: <https://doi.org/10.1145/3442188.3445922>

BENDER, E. M. You Are Not a Parrot And a chatbot is not a human. And a linguist named Emily M. Bender is very worried what will happen when we forget this. Disponível em: <https://nymag.com/intelligencer/article/ai-artificial-intelligence-chatbots-emily-m-bender.html>. Acesso em: 9 abr. 2023.

BENDER, E. M. Resisting Dehumanization in the Age of “AI”. Current Directions in Psychological Science, v. 0, n. 0, p. 09637214231217286, 2024.

BENDER, E. M.; FRIEDMAN, B. Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science. Transactions of the Association for Computational Linguistics, v. 6, p. 587–604, 2018.

BENDER, E. M.; KOLLER, A. Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Anais...Online: Association for Computational Linguistics, jul. 2020. Disponível em: <https://aclanthology.org/2020.acl-main.463>

BENNETT, A. Interruptions and the interpretation of conversation. Annual Meeting of the Berkeley Linguistics Society. Anais...1978. Disponível em: <https://doi.org/10.1080/01638538109544513>

BENOTTI, L.; BLACKBURN, P. Grounding as a Collaborative Process. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Anais...Online: Association for Computational Linguistics, abr. 2021. Disponível em: <https://aclanthology.org/2021.eacl-main.41>

BERG-KIRKPATRICK, T.; BURKETT, D.; KLEIN, D. An Empirical Investigation of Statistical Significance in NLP. Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. Anais...Jeju Island, Korea: Association for Computational Linguistics, jul. 2012. Disponível em: <https://aclanthology.org/D12-1091>

BERNARDO, S. Episódio e evento na organização tópica da conversa informal. Soletras, v. 1, p. 34–49, 2001.

BERNARDO, S. Então e agora na conversa informal. Soletras, v. 5-6, p. 65–81, 2003.

BERNARDO, S. Papel das formas O? H e O? H em turnos conversacionais. Revista do GELNE, v. 7, n. 1/2, p. 73–88, 2005.

BERNARDO, S. P. Foco e ponto de vista na organização conversacional. Pesquisas em Lingüística e Literatura: Descrição, Aplicação, Ensino - ISBN: 85-906478-0-3, 2002.

BERNARDO, S. P.; VELOZO, N. DE A.; ABREU, J. C. DE. Espaços mentais na conceptualização de conversa: dois modelos em análise. Revista do GELNE, v. 23, n. 1, p. 201–216, 2021.

BERNSEN, N. O.; DYBKJÆR, H.; DYBKJÆR, L. Cooperativity in human-machine and human-human spoken dialogue. Discourse processes, v. 21, n. 2, p. 213–236, 1996.

BERTAGLIA, T. F. C.; NUNES, M. DAS G. V. Exploring Word Embeddings for Unsupervised Textual User-Generated Content Normalization. Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT). Anais...Osaka, Japan: The COLING 2016 Organizing Committee, dez. 2016. Disponível em: <https://aclanthology.org/W16-3916>

BERTAGLIA, T. F. C.; NUNES, M. DAS G. V. Normalização textual de conteúdo gerado por usuário. mathesis—[s.l.] Universidade de São Paulo, 2017.

BERTOLDI, A. Os Limites da Criação Automática de Léxicos Computacionais Baseados em Frames: Um Estudo Contrastivo do Frame Criminal_process (The Limits of the Automatic Creation of Frame-based Computational Lexicons: a Contrastive Study of the Criminal_process Frame) [in Portuguese]. Proceedings of the 8th Brazilian Symposium in Information and Human Language Technology. Anais...2011. Disponível em: <https://aclanthology.org/W11-4510>

BIANCHI, F.; HOVY, D. On the Gap between Adoption and Understanding in NLP. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. Anais...Online: Association for Computational Linguistics, ago. 2021. Disponível em: <https://aclanthology.org/2021.findings-acl.340>

BICK, E. The Parsing System "Palavras": Automatic Grammatical Analysis of Portuguese in a Constraint Grammar Framework. tese de doutorado—[s.l.] Aarhus University Press, Denmark; University of Arhus, 2000.

BICK, E. A dependency-based approach to anaphora annotation. Proceedings of th 9th International Conference on Computational Processing of the Portuguese Language. Anais...Porto Alegre, Brazil: 2010.

BICK, E. S. PFN-PT: A Framenet Annotator for Portuguese: Anotação semântica automática: um novo Framenet para o português. Domínios de Linguagem, v. 16(4)7, p. 1401–1435, 2009.

BIDERMAN, M. T. C. Teoria linguística: linguística quantitativa e computacional. Rio de Janeiro: Martins Fontes, 1978.

BIRD, S. Decolonising Speech and Language Technology. Proceedings of the 28th International Conference on Computational Linguistics. Anais...Barcelona, Spain (Online): International Committee on Computational Linguistics, dez. 2020. Disponível em: <https://aclanthology.org/2020.coling-main.313>

BIRD, S.; LOPER, E. NLTK: The Natural Language Toolkit. Proceedings of the ACL Interactive Poster and Demonstration Sessions. Anais...Barcelona, Spain: Association for Computational Linguistics, jul. 2004. Disponível em: <https://aclanthology.org/P04-3031>

BIRON, T. et al. Automatic detection of prosodic boundaries in spontaneous speech. PLoS ONE, v. 16, n. 5, p. 1–21, maio 2021.

BIZER, C. et al. DBpedia: A crystallization point for the Web of Data. Web Semantics, 2009.

BLACKBURN, P.; BOS, J. Representation and Inference for Natural Language: A First Course in Computational Semantics. [s.l.] Center for the Study of Language; Information, 2005.

BOBROW, D. G. et al. GUS, a frame-driven dialog system. Artificial Intelligence, v. 8, n. 2, p. 155–173, 1977.

BOERSMA, P.; WEENINK, D. Praat: doing phonetics by computer [Computer program]. Version 6.3.10., 2023. Disponível em: <http://www.praat.org/>

BOGANTES, D. et al. Towards Lexical Encoding of Multi-Word Expressions in Spanish Dialects. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16). Anais...Portorož, Slovenia: European Language Resources Association (ELRA), 2016. Disponível em: <https://aclanthology.org/L16-1358>

BOJANOWSKI, P. et al. Enriching Word Vectors with Subword Information. Transactions of the Association for Computational Linguistics, v. 5, p. 135–146, 2017.

BOND, F.; FOSTER, R. Linking and extending an open multilingual wordnet. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Anais...Sofia, Bulgaria: Association for Computational Linguistics, ago. 2013. Disponível em: <https://aclanthology.org/P13-1133>

BOS, J. et al. Survey of existing interactive systems. Trindi (Task Oriented Instructional Dialogue) report, v. D1, p. 3, 1999.

BOTELHO, J. M. Conversação: Mudança e desvio de tópico conversacional. Revista Philologus, v. 17, n. 50, 2011.

BOTT, S. et al. GhoSt-PV: A Representative Gold Standard of German Particle Verbs. (M. Zock, A. Lenci, S. Evert, Eds.)Proceedings of the 5th Workshop on Cognitive Aspects of the Lexicon (CogALex - V). Anais...Osaka, Japan: The COLING 2016 Organizing Committee, dez. 2016. Disponível em: <https://aclanthology.org/W16-5318>

BOTZER, N. et al. TK-KNN: A Balanced Distance-Based Pseudo Labeling Approach for Semi-Supervised Intent Classification. (H. Bouamor, J. Pino, K. Bali, Eds.)Findings of the Association for Computational Linguistics: EMNLP 2023. Anais...Singapore: Association for Computational Linguistics, dez. 2023. Disponível em: <https://aclanthology.org/2023.findings-emnlp.429/>

BOUAMOR, D.; SEMMAR, N.; ZWEIGENBAUM, P. Identifying bilingual Multi-Word Expressions for Statistical Machine Translation. (N. C. (Conference. Chair) et al., Eds.)Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC’12). Anais...Istanbul, Turkey: European Language Resources Association (ELRA), maio 2012.

BOUAYAD-AGHA, N. et al. Content selection from semantic web data. INLG 2012 Proceedings of the Seventh International Natural Language Generation Conference. Anais...2012.

BOWMAN, S. R. et al. A large annotated corpus for learning natural language inference. Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Anais...Lisbon, Portugal: Association for Computational Linguistics, set. 2015. Disponível em: <https://aclanthology.org/D15-1075>

BOXER, D. Applying sociolinguistics: Domains and face-to-face interaction. [s.l.] John Benjamins Publishing, 2002. v. 15

BRAGGAAR, A. et al. Evaluating Task-oriented Dialogue Systems: A Systematic Review of Measures, Constructs and their Operationalisations. arXiv preprint arXiv:2312.13871, 2023.

BRANDOM, R. B. Articulating Reasons: An Introduction to Inferentialism. Cambridge, Massachusetts, EUA: Harvard University Press, 2001.

BRASCHLER, M.; PETERS, C. CLEF 2002 Methodology and Metrics. Em: PETERS, C. (Ed.). Advances in Cross-Language Information Retrieval: Results of the CLEF 2002 Evaluation Campaign. [s.l.] Springer, 2003. p. 512–525.

BRASCHLER, M.; PETERS, C. Cross-Language Evaluation Forum: Objectives, Results, Achievements. Information Retrieval, v. 7, n. 1-2, p. 7–31, 2004.

BRAUDE, D. A.; SHIMODAIRA, H.; YOUSSEF, A. B. Template-warping based speech driven head motion synthesis. Interspeech. Anais...2013.

BREEN, J. JMdict: a Japanese-Multilingual Dictionary. Proceedings of the Workshop on Multilingual Linguistic Resources. Anais...Geneva, Switzerland: COLING, 2004. Disponível em: <https://aclanthology.org/W04-2209>

BRENNAN, S. E.; GALATI, A.; KUHLEN, A. K. Two minds, one dialog: Coordinating speaking and understanding. Em: Psychology of learning and motivation. [s.l.] Elsevier, 2010. v. 53p. 301–344.

BREWSTER, C.; WILKS, Y. Ontologies, taxonomies, thesauri:learning from texts. (M. Deegan, Ed.)Proceedings of Use of Computational Linguistics in the Extraction of Keyword Information from Digital Library Content Workshop. Anais...2004. Disponível em: <http://www.cbrewster.com/papers/KeyWord_FMO.pdf>

BRILL, E. A Simple Rule-Based Part of Speech Tagger. Proceedings of the Third Conference on Applied Natural Language Processing. Anais...: ANLC ’92.USA: Association for Computational Linguistics, 1992. Disponível em: <https://doi.org/10.3115/974499.974526>

BRITO, I. A. et al. ToxSyn-PT: A Large-Scale Synthetic Dataset for Hate Speech Detection in Portuguese., 2025. Disponível em: <https://arxiv.org/abs/2506.10245>

BROWN, T. B. et al. Language Models are Few-Shot Learners. (H. Larochelle et al., Eds.)Advances in Neural Information Processing Systems. Anais...Curran Associates, Inc., 2020. Disponível em: <https://proceedings.neurips.cc/paper/2020/hash/1457c0d6bfcb4967418bfb8ac142f64a-Abstract.html>

BRUNEAU, T. J. Communicative silences: Forms and functions. Journal of communication, v. 23, n. 1, p. 17–46, 1973.

BUCKLEY, C.; VOORHEES, E. Evaluating Evaluation Measure Stability. Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Anais...2000. Disponível em: <https://sigir.org/wp-content/uploads/2017/06/p235.pdf>

BULHÕES, J. DO S. U. et al. Levantamento, análise e descrição de elementos paralinguı́sticos do português espontâneo. mathesis—[s.l.] Universidade Federal do Pará, 2006.

BUOLAMWINI, J.; GEBRU, T. Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. (S. A. Friedler, C. Wilson, Eds.)Proceedings of the 1st Conference on Fairness, Accountability and Transparency. Anais...: Proceedings of Machine Learning Research.PMLR, 2018. Disponível em: <https://proceedings.mlr.press/v81/buolamwini18a.html>

BUTNARIU, C. et al. SemEval-2 Task 9: The Interpretation of Noun Compounds Using Paraphrasing Verbs and Prepositions. Proceedings of the 5th International Workshop on Semantic Evaluation. Anais...Uppsala, Sweden: Association for Computational Linguistics, jul. 2010. Disponível em: <https://aclanthology.org/S10-1007>

CABRAL, L. et al. FakeWhastApp.BR: NLP and Machine Learning Techniques for Misinformation Detection in Brazilian Portuguese WhatsApp Messages. Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021) - Volume 1. Anais...2021.

CABRÉ, M. T. La terminología: representación y comunicación. [s.l.] Editora: Documenta Universitaria, 1999.

CAÇÃO, F. N. et al. DEEPAGÉ: Answering Questions in Portuguese About the Brazilian Environment. (A. Britto, K. Valdivia Delgado, Eds.)Intelligent Systems. Anais...Cham: Springer International Publishing, 2021.

CAFFERKEY, C.; HOGAN, D.; GENABITH, J. VAN. Multi-word units in treebank-based probabilistic parsing and generation. Proc. of RANLP 2007. Anais...Borovets: 2007.

CALLISON-BURCH, C. et al. Findings of the 2010 joint workshop on statistical machine translation and metrics for machine translation. Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR. Anais...2010.

CALZOLARI, N. et al. Towards best Practice for Multiword Expressions in Computational Lexicons. proc of the Third lrecconf (LREC 2002). Anais...Las Palmas, Canary Islands, Spain: elra, 2002.

CAMPOS, J. et al. Towards Fully Automated News Reporting in Brazilian Portuguese. Anais do XVII Encontro Nacional de Inteligência Artificial e Computacional. Anais...Porto Alegre, RS, Brasil: SBC, 2020. Disponível em: <https://sol.sbc.org.br/index.php/eniac/article/view/12158>

CAMPRESS (ED.). Cambridge International Dictionary of Phrasal Verbs. Cambridge, UK: campress, 1997.

CANDIDO JUNIOR, A. et al. CORAA: a large corpus of spontaneous and prepared speech manually validated for speech recognition in Brazilian Portuguese. CoRR, v. abs/2110.15731, 2021.

CANDIDO JUNIOR, A. et al. CORAA ASR: a large corpus of spontaneous and prepared speech manually validated for speech recognition in Brazilian Portuguese. Language Resources & Evaluation, 2022.

CANDITO, M. et al. A French corpus annotated for multiword expressions and named entities. Journal of Language Modelling, v. 8, n. 2, p. 415–479, 2021.

CANDITO, M.; CONSTANT, M. Strategies for Contiguous Multiword Expression Analysis and Dependency Parsing. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Anais...Baltimore, Maryland: Association for Computational Linguistics, jun. 2014. Disponível em: <https://aclanthology.org/P14-1070>

CAP, F. et al. How to Produce Unseen Teddy Bears: Improved Morphological Processing of Compounds in SMT. Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL). Anais...Goteborg, Sweden: 2014.

CARAPINHA, C.; PLAG, C. A interação verbal em sala de audiências: turn design. Actas do XIII Congreso Internacional de Lingüı́stica Xeral: Vigo, 13-15 de xuño de 2018. Anais...Universidade de Vigo, 2018. Disponível em: <http://cilx2018.uvigo.gal/actas/pdf/661468.pdf>

CARDOSO, N. Avaliação de Sistemas de Reconhecimento de Entidades Mencionadas. mathesis—[s.l.] Faculdade de Engenharia da Universidade do Porto, 2006.

CARDOSO, N. Rembrandt - a named-entity recognition framework. Proceedings of the Eighth International Conference on Language Resources and Evaluation. Anais...Istanbul, Turkey: 2012. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2012/summaries/409.html>

CARDOSO, P. C. F. et al. CSTNews-a discourse-annotated corpus for single and multi-document summarization of news texts in Brazilian Portuguese. Proceedings of the 3rd RST Brazilian Meeting. Anais...2011.

CARDOSO, P. C. F. Exploração de métodos de sumarização automática multidocumento com base em conhecimento semântico-discursivo. tese de doutorado—[s.l.] (Doutorado em Ciências de Computação e Matemática Computacional) - Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, 2014.

CARLSON, L.; MARCU, D. Discourse tagging reference manual. ISI Technical Report ISI-TR-545, v. 54, n. 2001, p. 56, 2001.

CARPUAT, M.; DIAB, M. Task-based Evaluation of Multiword Expressions: a Pilot Study in Statistical Machine Translation. Proceedings of HLT: The 2010 Annual Conference of the North American Chapter of the ACL (NAACL 2003). Anais...Los Angeles, California: ACL, jun. 2010.

CARVALHO, G.; MATOS, D. M. DE; ROCIO, V. IdSay: Question Answering for Portuguese. (C. Peters et al., Eds.)Evaluating Systems for Multilingual and Multimodal Information Access. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

CARVALHO, M. W. P. L.; ACIOLI, M. D. Entre falas simultâneas, tomadas de turno e sobreposição de vozes: quem tem a palavra no debate? Revista do GELNE, v. 19, p. 155–165, 2017.

CASANOVA, E. Síntese de voz aplicada ao português brasileiro usando aprendizado profundo. {B.S.} thesis—[s.l.] Universidade Tecnológica Federal do Paraná, 2019.

CASANOVA, E. et al. TTS-Portuguese Corpus: a corpus for speech synthesis in Brazilian Portuguese. Language Resources and Evaluation, v. 56, n. 3, p. 1043–1055, 2022.

CASANOVA, E.; SHULBY, C. D.; ALUÍSIO, S. M. Deep learning approaches for speech synthesis and speaker verification. Acoustic communication: an interdisciplinary approach, 2021.

CASELI, H. DE M.; FREITAS, C.; VIOLA, R. Processamento de Linguagem Natural. Em: Tópicos em Gerenciamento de Dados e Informações: Minicursos do SBBD 2022. [s.l.] Sociedade Brasileira de Computação, 2022. p. 1–28.

CASTILHO, A. T. DE. O português culto falado no Brasil: história do Projeto NURC. Em: PRETI, D.; URBANO, H. (Eds.). A linguagem falada culta na cidade de São Paulo. São Paulo, SP: TAQ/Fapesp, 1990. v. 4 – Estudosp. 141–292.

CASTILHO, A. T. DE. Gramática do Português Brasileiro: fundamentos, perspectivas. Cadernos de Linguística, v. 2, n. 1, p. e252, abr. 2021.

CASTRO FERREIRA, T. et al. NeuralREG: An end-to-end approach to referring expression generation. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Anais...Melbourne, Australia: Association for Computational Linguistics, 2018. Disponível em: <http://aclweb.org/anthology/P18-1182>

CASTRO FERREIRA, T. et al. Neural data-to-text generation: A comparison between pipeline and end-to-end architectures. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Anais...Hong Kong, China: Association for Computational Linguistics, nov. 2019. Disponível em: <https://www.aclweb.org/anthology/D19-1052>

CASTRO FERREIRA, T. et al. Evaluating Recognizing Question Entailment Methods for a Portuguese Community Question-Answering System about Diabetes Mellitus. (R. Mitkov, G. Angelova, Eds.)Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021). Anais...Held Online: INCOMA Ltd., set. 2021. Disponível em: <https://aclanthology.org/2021.ranlp-1.28>

CASTRO FERREIRA, T.; PARABONI, I. Referring Expression Generation: Taking Speakers’ Preferences into Account. Em: SOJKA, P. et al. (Eds.). Text, Speech and Dialogue. Lecture Notes em Computer Science. [s.l.] Springer International Publishing, 2014a. v. 8655p. 539–546.

CASTRO FERREIRA, T.; PARABONI, I. Classification-based Referring Expression Generation. Computational Linguistics and Intelligent Text Processing (CICLing-2014), Lecture Notes in Computer Science 8403. Anais...Kathmandu, Nepal: Springer, b2014.

CAVALIERE, P.; ROMEO, G. From Poisons to Antidotes: Algorithms as Democracy Boosters. European Journal of Risk Regulation, v. 13, n. 3, p. 421–442, 2022.

CERVONE, A.; STEPANOV, E.; RICCARDI, G. Coherence Models for Dialogue. Proc. Interspeech 2018. Anais...2018. Disponível em: <https://10.21437/Interspeech.2018-2446>

CHALAMALASETTI, K. et al. clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents. (H. Bouamor, J. Pino, K. Bali, Eds.)Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Anais...Singapore: Association for Computational Linguistics, dez. 2023. Disponível em: <https://aclanthology.org/2023.emnlp-main.689>

CHANDRAN, R. Indigenous groups in NZ, US fear colonisation as AI learns their languages. Disponível em: <https://www.context.news/ai/nz-us-indigenous-fear-colonisation-as-bots-learn-their-languages>. Acesso em: 7 abr. 2023.

CHANG, K.-W. et al. Illinois-Coref: The UI system in the CoNLL-2012 shared task. Joint Conference on EMNLP and CoNLL-Shared Task. Anais...Association for Computational Linguistics, 2012.

CHAPELLE, O.; SCHOLKOPF, B.; ZIEN, A. Semi-Supervised Learning. [s.l.] The MIT Press, 2006.

CHARPENTIER, F.; STELLA, M. Diphone synthesis using an overlap-add technique for speech waveforms concatenation. ICASSP’86. IEEE International Conference on Acoustics, Speech, and Signal Processing. Anais...IEEE, 1986.

CHE, X. et al. Punctuation Prediction for Unsegmented Transcript Based on Word Vector. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16). Anais...Portorož, Slovenia: European Language Resources Association (ELRA), 2016. Disponível em: <https://aclanthology.org/L16-1103>

CHEN, K.; HASEGAWA-JOHNSON, M. A. How prosody improves word recognition. Speech Prosody 2004. Anais...2004.

CHEN, L.-W.; RUDNICKY, A. Exploring Wav2vec 2.0 Fine Tuning for Improved Speech Emotion Recognition. ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Anais...IEEE, 2023.

CHINCHOR, N. The statistical significance of the MUC-4 results. Proceedings of the Fourth Message Understanding Conference (MUC-4). Anais...Morgan Kaufmann Publ., 1992. Disponível em: <https://dl.acm.org/doi/pdf/10.3115/1072064.1072068>

CHISHOLM, A.; RADFORD, W.; HACHEY, B. Learning to generate one-sentence biographies from Wikidata. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers. Anais...: EACL’17.Valencia, Spain: Association for Computational Linguistics, 2017. Disponível em: <http://aclanthology.coli.uni-saarland.de/pdf/E/E17/E17-1060.pdf>

CHOUEKA, Y. Looking for Needles in a Haystack or Locating Interesting Collocational Expressions in Large Textual Databases. (C. Fluhr, D. E. Walker, Eds.)Proceedings of the 2nd International Conference on Computer-Assisted Information Retrieval (Recherche d’Information et ses Applications - RIA 1988). Anais...Cambridge, MA, USA: CID, 1988.

CHOVIL, N. Discourse-oriented facial displays in conversation. Research on Language & Social Interaction, v. 25, n. 1-4, p. 163–194, 1991.

CHUNG, Y.-A.; GLASS, J. Speech2Vec: A Sequence-to-Sequence Framework for Learning Word Embeddings from Speech. Proc. Interspeech 2018. Anais...2018.

CHURCH, K. How many multiword expressions do people know? tslp Special Issue on mwes: from theory to practice and use, part 1 (TSLP), v. 10, n. 2, 2013.

CIERI, C.; MILLER, D.; WALKER, K. The Fisher Corpus: a Resource for the Next Generations of Speech-to-Text. Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04). Anais...Lisbon, Portugal: European Language Resources Association (ELRA), 2004. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2004/pdf/767.pdf>

CLARK, E. V. Conversational repair and the acquisition of language. Discourse Processes, v. 57, n. 5-6, p. 441–459, 2020.

CLARK, H. H. Arenas of language use. [s.l.] University of Chicago Press, 1992.

CLARK, H. H. Using language. [s.l.] Cambridge University Press, 1996b.

CLARK, H. H. Communities, commonalities, and communication. Em: Rethinking linguistic relativity. [s.l.] Cambridge University Press, 1996a. v. 17p. 324–355.

CLARK, H. H. How to talk with children. Em: Language in Interaction. [s.l.] John Benjamins, 2014. p. 333–352.

CLARK, H. H.; BRENNAN, S. E. Grounding in communication. Em: Perspectives on socially shared cognition. [s.l.] American Psychological Association, 1991. p. 127–149.

CLARK, H. H.; SCHAEFER, E. F. Collaborating on contributions to conversations. Language and cognitive processes, v. 2, n. 1, p. 19–41, 1987.

CLARK, H. H.; TREE, J. E. F. Using uh and um in spontaneous speaking. Cognition, v. 84, n. 1, p. 73–111, 2002.

CLARK, H. H.; WILKES-GIBBS, D. Referring as a collaborative process. Cognition, v. 22, n. 1, p. 1–39, 1986.

CLERWALL, C. Enter the Robot Journalist. Journalism Practice, v. 8, n. 5, p. 519–531, 2014.

CLIFTON, A. et al. 100,000 podcasts: A spoken English document corpus. Proceedings of the 28th International Conference on Computational Linguistics. Anais...2020.

COECKELBERGH, M. Artificial Intelligence, Responsibility Attribution, and a Relational Justification of Explainability. Science and Engineering Ethics, v. 26, p. 2051–2068, 2020.

COELHO DA SILVA, T.; FERNANDES DE MACÊDO, J.; MAGALHÃES, R. Tracking the Evolution of Covid-19 Symptoms through Clinical Conversations. Proceedings of the 5th Clinical Natural Language Processing Workshop. Anais...Toronto, Canada: Association for Computational Linguistics, jul. 2023. Disponível em: <https://aclanthology.org/2023.clinicalnlp-1.6>

COELHO, G. E.; SERRALHEIRO, A. J.; NETO, J. P. A spoken dialog system speech interface based on a microphone array. Computational Processing of the Portuguese Language: 8th International Conference, PROPOR 2008 Aveiro, Portugal, September 8-10, 2008 Proceedings 8. Anais...Springer, 2008. Disponível em: <https://doi.org/10.1007/978-3-540-85980-2_3>

COHEN, J. A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement, v. 20, n. 1, p. 37–46, 1960.

COHEN, K. B. et al. Three Dimensions of Reproducibility in Natural Language Processing. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018). Anais...Miyazaki, Japan: European Language Resources Association (ELRA), 2018. Disponível em: <https://aclanthology.org/L18-1025>

COHEN, P. R.; HOWE, A. E. How Evaluation Guides AI Research: The Message Still Counts More than the Medium. AI Magazine, v. 9, n. 4, p. 35, 1988.

COLLOVINI, S. et al. Summ-it: Um Corpus Anotado com Informações Discursivas Visando a Sumarização Automática. Proceedings of V Workshop em Tecnologia da Informação e da Linguagem Humana. Anais...Rio de Janeiro, Brasil: 2007.

COLLOVINI, S. et al. Extraction of Relation Descriptors for Portuguese Using Conditional Random Fields. Proceedings of the 14th Ibero-American Conference on Advances in Artificial Intelligence. Anais...Santiago de Chile: 2014.

COLLOVINI, S. et al. IberLEF 2019 Portuguese Named Entity Recognition and Relation Extraction Tasks. Proceedings of the Iberian Languages Evaluation Forum co-located with 35th Conference of the Spanish Society for Natural Language Processing. Anais...2019. Disponível em: <http://ceur-ws.org/Vol-2421/NER\_Portuguese\_overview.pdf>

COMMISSION, E. Proposal for a Regulation laying down harmonised rules on artificial intelligence. Disponível em: < https://digital-strategy.ec.europa.eu/en/library/proposal-regulation-laying-down-harmonised-rules-artificial-intelligence >. Acesso em: 28 ago. 2023.

CONSTANT, M. et al. Multiword Expression Processing: A Survey. Computational Linguistics, 2017.

CONSTANT, M.; NIVRE, J. A Transition-Based System for Joint Lexical and Syntactic Analysis. Proc. of ACL 2016. Anais...Berlin: 2016.

COPESTAKE, A. et al. Minimal recursion semantics: An introduction. Research on language and computation, v. 3, p. 281–332, 2005.

CORDEIRO, S. R. et al. Unsupervised Compositionality Prediction of Nominal Compounds. Computational Linguistics, v. 45, n. 1, p. 1–57, 2019.

COREIXAS, T. Resolução De Correferência E Categorias De Entidades Nomeadas. Dissertação de Mestrado, Pontifı́cia Universidade Católica do Rio Grande do Sul, 2010.

CORRÊA, N. K. et al. Worldwide AI ethics: A review of 200 guidelines and recommendations for AI governance. Patterns, v. 4, n. 10, p. 100857, 2023.

CORRÊA, N. K. et al. Tucano: Advancing neural text generation for Portuguese. Patterns, p. 101325, jul. 2025.

CORRÊA, U. B. et al. Overview of the IDPT Task on Irony Detection in Portuguese at IberLEF 2021. Procesamiento del Lenguaje Natural, v. 67, p. 269–276, 2021.

CORTES, E. et al. An Empirical Comparison of Question Classification Methods for Question Answering Systems. (N. Calzolari et al., Eds.)Proceedings of the Twelfth Language Resources and Evaluation Conference. Anais...Marseille, France: European Language Resources Association, 2020. Disponível em: <https://aclanthology.org/2020.lrec-1.665>

CORTES, E. G.; WOLOSZYN, V.; BARONE, D. A. C. When, Where, Who, What or Why? A Hybrid Model to Question Answering Systems. (A. Villavicencio et al., Eds.)Computational Processing of the Portuguese Language. Anais...Cham: Springer International Publishing, 2018.

COSTA, L. F. Using Answer Retrieval Patterns to Answer Portuguese Questions. (C. Peters et al., Eds.)Evaluating Systems for Multilingual and Multimodal Information Access. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2009.

COSTA, L. F.; CABRAL, L. M. Answering Portuguese Questions. (A. Teixeira et al., Eds.)Computational Processing of the Portuguese Language. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2008.

COSTA, P. B. DA; PARABONI, I. Transferência de estilo textual arbitrário em português. Linguamática, v. 15, n. 2, p. 19–36, 2023.

COSTA, P. B. DA; PARABONI, I. Sequence-to-sequence and transformer approaches to Portuguese text style transfer. Proceedings of the 16th International Conference on Computational Processing of Portuguese. Anais...Santiago de Compostela, Galicia/Spain: Association for Computational Lingustics, mar. 2024. Disponível em: <https://aclanthology.org/2024.propor-1.54>

COSTA, P.; PARABONI, I. Personality-dependent Neural Text Summarization. Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019). Anais...2019.

COUCKE, A. et al. Snips voice platform: an embedded spoken language understanding system for private-by-design voice interfaces. arXiv preprint arXiv:1805.10190, 2018.

COUILLAULT, A. et al. Evaluating corpora documentation with regards to the Ethics and Big Data Charter. Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14). Anais...Reykjavik, Iceland: European Language Resources Association (ELRA), 2014. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2014/pdf/424_Paper.pdf>

CRESTI, E. et al. The C-ORAL-ROM CORPUS. A Multilingual Resource of Spontaneous Speech for Romance Languages. Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04). Anais...Lisbon, Portugal: European Language Resources Association (ELRA), 2004. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2004/pdf/357.pdf>

CRISTEA, D.; IDE, N.; ROMARY, L. Veins theory: A model of global discourse cohesion and coherence. Coling-ACL Conference. Anais...1998.

CROCKER, M. W. Computational psycholinguistics. The handbook of computational linguistics and natural language processing, p. 482–513, 2010.

CRUSE, D. A. Lexical Semantics. Cambridge, UK: campress, 1986.

CRUZ, B. S. Concessionária do Metrô de SP é processada por ter câmeras que leem nossas emoções. Disponível em: < https://www.uol.com.br/tilt/noticias/redacao/2018/08/31/concessionaria-do-metro-de-sp-e-processada-por-ter-cameras-que-leem-emocoes.htm >. Acesso em: 29 ago. 2023.

CRUZ, B. S. Racismo Calculado. Disponível em: < https://www.uol.com.br/tilt/reportagens-especiais/como-os-algoritmos-espalham-racismo/#cover >. Acesso em: 29 ago. 2023.

CRUZ, J. A. DA et al. Creating an Academic Conversational Agent for Dynamic Information Retrieval. Proceedings of the XVI Brazilian Symposium on Information Systems. Anais...: SBSI ’20.New York, NY, USA: Association for Computing Machinery, 2020. Disponível em: <https://doi.org/10.1145/3411564.3411647>

CUNHA RECUERO, R. DA. Elementos para a análise da conversação na comunicação mediada pelo computador. Verso e Reverso, v. 22, 2008.

DAHL, V. Natural language processing and logic programming. Journal of Logic Programming, v. 19-20, n. 1, p. 681–714, 1994.

DALE, R.; HADDOCK, N. Generating referring expressions involving relations. Proceedings of the fifth conference on European chapter of the Association for Computational Linguistics. Anais...: EACL’91.Berlin, Germany: Association for Computational Linguistics, 1991.

DANESCU-NICULESCU-MIZIL, C. et al. Echoes of power: Language effects and power differences in social interaction. Proceedings of the 21st international conference on World Wide Web. Anais...2012. Disponível em: <https://doi.org/10.1145/2187836.2187931>

DANTAS, A. C. et al. AstroBot: Um chatbot com inteligência artificial para auxiliar no processo de ensino e aprendizagem de fı́sica. Anais dos Workshops do Congresso Brasileiro de Informática na Educação. Anais...2019. Disponível em: <https://doi.org/10.5753/cbie.wcbie.2019.1196>

DE PAIVA, V. et al. An overview of Portuguese wordnets. Proceedings of the 8th Global WordNet Conference (GWC). Anais...2016.

DE PAIVA, V.; RADEMAKER, A.; MELO, G. DE. OpenWordNet-PT: An Open Brazilian Wordnet for Reasoning. Proceedings of COLING 2012: Demonstration Papers. Anais...2012.

DEEMTER, K. VAN. Designing Algorithms for Referring with Proper Names. Proceedings of the 9th International Natural Language Generation conference. Anais...: INLG’16.Edinburgh, UK: Association for Computational Linguistics, a2016. Disponível em: <http://www.aclweb.org/anthology/W16-6605>

DEEMTER, K. VAN. Computational Models of Referring. A Study in Cognitive Science. Cambridge, Massachusetts, USA: MIT Press, 2016b.

DEMPSEY, P. The teardown: Google Home personal assistant. Engineering & Technology, v. 12, n. 3, p. 80–81, 2017.

DERIU, J. et al. Survey on evaluation methods for dialogue systems. Artificial Intelligence Review, v. 54, p. 755–810, 2021.

DEVLIN, J. et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. (J. Burstein, C. Doran, T. Solorio, Eds.)Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2019. Anais...Minneapolis, MN, USA: Association for Computational Linguistics, 2019. Disponível em: <https://doi.org/10.18653/v1/n19-1423>

DHUMAL DESHMUKH, R.; KIWELEKAR, A. Deep Learning Techniques for Part of Speech Tagging by Natural Language Processing. 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). Anais...mar. 2020.

DI FELIPPO, A. et al. The DANTEStocks Corpus: an analysis of the distribution of Universal Dependencies-based Part-of-Speech tags. Revista da ABRALIN, v. 22, n. 2, p. 249–271, 2024.

DI GANGI, M. A. et al. MuST-C: a Multilingual Speech Translation Corpus. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Anais...Minneapolis, Minnesota: Association for Computational Linguistics, jun. 2019. Disponível em: <https://aclanthology.org/N19-1202>

DIAS-DA-SILVA, B. C. A face tecnológica dos estudos da linguagem: o processamento automático das lı́nguas naturais. 1996. 272f. tese de doutorado—[s.l.] Tese (Doutorado em Lingüı́stica e Lı́ngua Portuguesa)–Faculdade de Ciências e …, 1996.

DIAS-DA-SILVA, B. C. Wordnet.Br: An Exercise of Human Language Technology Research. Proceedings of the Third International WordNet Conference. Anais...2005. Disponível em: <http://semanticweb.kaist.ac.kr/conference/gwc/pdf2006/6.pdf>

DODDINGTON, G. et al. The Automatic Content Extraction (ACE) Program: Tasks, Data, and Evaluation. (M. T. Lino et al., Eds.)Proceedings of LREC’2004, Fourth International Conference on Language resources and Evaluation (Lisboa, 26-28 May 2004). Anais...2004. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2004/pdf/5.pdf>

DODGE, J. et al. Show Your Work: Improved Reporting of Experimental Results. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Anais...Hong Kong, China: Association for Computational Linguistics, nov. 2019. Disponível em: <https://aclanthology.org/D19-1224>

DONG, L. et al. Learning to Generate Product Reviews from Attributes. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers. Anais...: EACL’17.Valencia, Spain: Association for Computational Linguistics, 2017. Disponível em: <http://aclanthology.coli.uni-saarland.de/pdf/E/E17/E17-1059.pdf>

DROR, R. et al. The Hitchhiker’s Guide to Testing Statistical Significance in Natural Language Processing. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Anais...Melbourne, Australia: Association for Computational Linguistics, jul. 2018. Disponível em: <https://aclanthology.org/P18-1128>

DROR, R. et al. Statistical significance testing for natural language processing. [s.l.] Springer, 2020.

DU BOIS, J. W. et al. Santa Barbara corpus of spoken American English. Parts 1–4. Philadelphia: Linguistic Data Consortium, 2000--2005.

DU BOIS, J. W. et al. Discourse transcription. Santa Barbara: Department of Linguistics, University of California, 1992. v. 4

DUMA, D.; KLEIN, E. Generating Natural Language from Linked Data: Unsupervised template extraction. Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers. Anais...Potsdam, Germany: Association for Computational Linguistics, 2013. Disponível em: <http://www.aclweb.org/anthology/W13-0108>

DUNCAN, S. Some signals and rules for taking speaking turns in conversations. Journal of personality and social psychology, v. 23, n. 2, p. 283, 1972.

DUNIETZ, J. The field of natural language processing is chasing the wrong goal. MIT Technology Review, 2020.

DURAN, M. S. et al. The Dawn of the Porttinari Multigenre Treebank: Introducing its Journalistic Portion. Anais do XIV Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana. Anais...Porto Alegre, RS, Brasil: SBC, 2023. Disponível em: <https://sol.sbc.org.br/index.php/stil/article/view/25443>

DURAN, M. S.; ALUÍSIO, S. M. Propbank-Br: a Brazilian Treebank Annotated with Semantic Role Labels. Proceedings of the 8th International Conference on Language Resources and Evaluation - LREC. Anais...2012.

DUŠEK, O.; NOVIKOVA, J.; RIESER, V. Findings of the E2E NLG challenge. arXiv preprint arXiv:1810.01170, 2018.

EBDEN, P.; SPROAT, R. The Kestrel TTS text normalization system. Natural Language Engineering, v. 21, p. 333–353, maio 2014.

EDMONDS, P.; KILGARRIFF, A. Introduction to the special issue on evaluating word sense disambiguation systems. Natural Language Engineering, v. 8, n. 4, p. 279–291, 2002.

EIJCK, J. VAN; UNGER, C. Computational Semantics with Functional Programming. [s.l.] Cambridge University Press, 2010.

EKMAN, P. An argument for basic emotions. Cognition and Emotion, v. 6, n. 3-4, p. 169–200, 1992.

EL AYADI, M.; KAMEL, M. S.; KARRAY, F. Survey on speech emotion recognition: Features, classification schemes, and databases. Pattern recognition, v. 44, n. 3, p. 572–587, 2011.

EMPOLI, G. DA. Os engenheiros do caos: Como as fake news, as teorias da conspiração e os algoritmos estão sendo utilizados para disseminar ódio, medo e influenciar eleições. [s.l.] Vestígio Editora, 2019.

ENGELMANN, D. C. et al. A conversational agent to support hospital bed allocation. Brazilian Conference on Intelligent Systems. Anais...Springer, 2021. Disponível em: <https://doi.org/10.1007/978-3-030-91702-9_1>

ERYIǦIT, G. et al. Annotation and Extraction of Multiword Expressions in Turkish Treebanks. Proceedings of the 11th Workshop on Multiword Expressions. Anais...Denver, Colorado: Association for Computational Linguistics, jun. 2015. Disponível em: <https://aclanthology.org/W15-0912>

ESSENFELDER, R.; RODRIGUES, V. P. Seqüências inseridas: fluência e disfluência em uma conversação espontânea. Revista Virtual de Estudos da Linguagem–ReVEL, v. 3, n. 4, 2005.

ETHAYARAJH, K.; JURAFSKY, D. Utility is in the Eye of the User: A Critique of NLP Leaderboards. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Anais...Online: Association for Computational Linguistics, nov. 2020. Disponível em: <https://aclanthology.org/2020.emnlp-main.393>

EVERT, S. Corpora and collocations. Em: LÜDELING, A.; KYTÖ, M. (Eds.). Corpus Linguistics: An International Handbook. [s.l.] De Gruyter Mouton, 2009. v. 2p. 1212–1248.

EVERT, S.; KRENN, B. Methods for the Qualitative Evaluation of Lexical Association Measures. Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics. Anais...Toulouse, France: Association for Computational Linguistics, jul. 2001. Disponível em: <https://aclanthology.org/P01-1025>

FARAHMAND, M.; SMITH, A.; NIVRE, J. A Multiword Expression Data Set: Annotating Non-Compositionality and Conventionalization for English Noun Compounds. proc of the 11th Workshop on mwes (MWE 2015). Anais...Denver, Colorado, USA: acl, 2015. Disponível em: <http://aclweb.org/anthology/W15-0904>

FÁVERO, L. L.; ANDRADE, M. L. DA C. V. DE O.; AQUINO, Z. G. O. DE. Perguntas e respostas como mecanismos de coesão e coerência no texto falado. Gramática do português falado, v. 4, p. 473–508, 1996.

FÁVERO, L. L.; ANDRADE, M. L. DA C. V. DE O.; AQUINO, Z. G. O. DE. Discurso e interação: a reformulação nas entrevistas. DELTA: Documentação de Estudos em Lingüı́stica Teórica e Aplicada, v. 14, p. 91–103, 1998.

FAYEK, H. M. Speech Processing for Machine Learning: Filter banks, Mel-Frequency Cepstral Coefficients (MFCCs) and What’s In-Between., 2016. Disponível em: <https://haythamfayek.com/2016/04/21/speech-processing-for-machine-learning.html>

FELLBAUM, C. WordNet: An Electronic Lexical Database. [s.l.] The MIT Press, 1998.

FERLA, J. R. Discurso reportado em narrativas: a construção colaborativa de histórias na fala-em-interação. Trabalho de conclusão de curso. Universidade do Vale do Rio dos Sinos, 2020.

FERNANDES, E. R.; SANTOS, C. N. DOS; MILIDIÚ, R. L. Latent trees for coreference resolution. Computational Linguistics, 2014.

FERNANDES, U. DA S. et al. Analyzing MoLIC’s Applicability to Model the Interaction of Conversational Agents: A Case Study on ANA Chatbot. Proceedings of the XX Brazilian Symposium on Human Factors in Computing Systems. Anais...: IHC ’21.New York, NY, USA: Association for Computing Machinery, 2021. Disponível em: <https://doi.org/10.1145/3472301.3484367>

FERRADEIRA, J. E. DE S. Resolução de anáfora pronominal. mathesis—[s.l.] Universidade Nova de Lisboa; Dissertação de Mestrado, Universidade Nova de Lisboa, 1993.

FERREIRA, A. et al. Agentes de conversação para idosos, plataforma Guardião. Anais Estendidos do XVIII Simpósio Brasileiro sobre Fatores Humanos em Sistemas Computacionais. Anais...Porto Alegre, RS, Brasil: SBC, 2019. Disponível em: <https://sol.sbc.org.br/index.php/ihc_estendido/article/view/8386>

FERREIRA, F.; SWETS, B. How incremental is language production? Evidence from the production of utterances requiring the computation of arithmetic sums. Journal of Memory and Language, v. 46, n. 1, p. 57–84, 2002.

FERREIRA, T. C. Advances in Natural Language Generation: Generating varied outputs from semantic inputs. tese de doutorado—[s.l.] Tilburg University, 2018.

FERREIRA, T. C. et al. The 2020 bilingual, bi-directional webnlg+ shared task overview and evaluation results (webnlg+ 2020). Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+). Anais...2020.

FILLMORE, C. J. et al. Frame semantics and the nature of language. Annals of the New York Academy of Sciences: Conference on the origin and development of language and speech. Anais...New York, 1976.

FILLMORE, C. J.; KAY, P.; O’CONNOR, M. C. Regularity and Idiomaticity in Grammatical Constructions: The Case of Let Alone. Language, v. 64, p. 501–538, 1988.

FINCH, S. E.; CHOI, J. D. Towards Unified Dialogue System Evaluation: A Comprehensive Analysis of Current Evaluation Protocols. Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue. Anais...1st virtual meeting: Association for Computational Linguistics, jul. 2020. Disponível em: <https://aclanthology.org/2020.sigdial-1.29>

FINLAYSON, M.; KULKARNI, N. Detecting Multi-Word Expressions Improves Word Sense Disambiguation. Proc. of the ACL 2011 Workshop on MWEs. Anais...Portland, OR: 2011.

FIRTH, J. R. The technique of semantics. Transactions of the philological society, v. 34, n. 1, p. 36–73, 1957.

FLAKE, J. K.; FRIED, E. I. Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them. Advances in Methods and Practices in Psychological Science, v. 3, n. 4, p. 456–465, 2020.

FLEISS, J. L. Measuring nominal scale agreement among many raters. Psychological Bulletin, v. 76, n. 5, p. 378–382, 1971.

FOKKENS, A. et al. Offspring from Reproduction Problems: What Replication Failure Teaches Us. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Anais...Sofia, Bulgaria: Association for Computational Linguistics, ago. 2013. Disponível em: <https://aclanthology.org/P13-1166>

FONSECA, E. B. Resolução de correferências em língua portuguesa: pessoa, local e organização. Dissertação de Mestrado, Pontifı́cia Universidade Católica do Rio Grande do Sul, 2014.

FONSECA, E. B. et al. Summ-it++: an enriched version of the summ-it corpus. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16). Anais...a2016.

FONSECA, E. B. Resolução de correferência nominal usando semântica em língua portuguesa. tese de doutorado—[s.l.] Pontifícia Universidade Católica do Rio Grande do Sul; Pontifı́cia Universidade Católica do Rio Grande do Sul, 2018.

FONSECA, E. B.; VIEIRA, R.; VANIN, A. Dealing With Imbalanced Datasets For Coreference Resolution. Proceedings of The Twenty-Eighth International Flairs Conference. Anais...a2015.

FONSECA, E. B.; VIEIRA, R.; VANIN, A. Adapting an Entity Centric Model for Portuguese Coreference Resolution. Portorož, Slovenia, c2016.

FONSECA, E. B.; VIEIRA, R.; VANIN, A. CORP: Coreference Resolution for Portuguese., b2016.

FONSECA, E. B.; VIEIRA, R.; VANIN, A. A. Coreference Resolution In Portuguese: Detecting Person, Location And Organization. Journal of the Brazilian Computational Intelligence Society, v. 12, n. 2, p. 86–97, 2014.

FONSECA, E. R. et al. Visão geral da avaliação de similaridade semântica e inferência textual. Linguamática, v. 8, n. 2, p. 3–13, d2016.

FONSECA, E. R.; ROSA, J. L. G. Mac-Morpho Revisited: Towards Robust Part-of-Speech Tagging. Proceedings of the 9th Brazilian Symposium in Information and Human Language Technology. Anais...2013. Disponível em: <https://aclanthology.org/W13-4811>

FONSECA, E. R.; ROSA, J. L.; ALUÍSIO, S. M. Evaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese. Journal of the Brazilian Computer Society, v. 21, n. 1, p. 32–38, fev. b2015.

FONSECA, E.; VANIN, A.; VIEIRA, R. Mention clustering to improve portuguese semantic coreference resolution. International Conference on Applications of Natural Language to Information Systems. Anais...Springer, 2018.

FORT, K.; ADDA, G.; COHEN, K. B. Last Words: Amazon Mechanical Turk: Gold Mine or Coal Mine? Computational Linguistics, v. 37, n. 2, p. 413–420, jun. 2011.

FORTE MARTINS, A. D. et al. Detection of misinformation about covid-19 in Brazilian Portuguese WhatsApp messages. International Conference on Applications of Natural Language to Information Systems. Anais...Springer, 2021.

FREGE, G. Über Sinn und Bedeutung. Zeitschrift für Philosophie und philosophische Kritik, v. 100, p. 25–50, 1892/19601892/1960.

FREIRE, P. Pedagogia do Oprimido. Rio de Janeiro: Paz e Terra/SA, 1989.

FREITAS, C. et al. Relações semânticas do ReRelEM: além das entidades no Segundo HAREM. Em: MOTA, C.; SANTOS, D. (Eds.). Desafios na avaliação conjunta do reconhecimento de entidades mencionadas. [s.l.] Linguateca, 2008a. p. 77–96.

FREITAS, C. et al. Relation detection between named entities: report of a shared task. Proceedings of the Workshop on Semantic Evaluations: Recent Achievements and Future Directions. Anais...Boulder, Colorado: b2009.

FREITAS, C. et al. Detection of relations between named entities: report of a shared task. Proceedings of the NAACL HLT Workshop on Semantic Evaluations: Recent Achievements and Future Directions, SEW-2009. Anais...Boulder, Colorado, USA: a2009. Disponível em: <https://comum.rcaap.pt/bitstream/10400.26/20504/1/FreitasetalSEW2009.pdf>

FREITAS, C. et al. Second HAREM: Advancing the State of the Art of Named Entity Recognition in Portuguese. Proceedings of the International Conference on Language Resources and Evaluation. Anais...Valletta, Malta: 2010. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2010/summaries/412.html>

FREITAS, C. et al. O que é uma resposta? Notas de uns avaliadores estafados. Linguamática, v. 4, n. 1, p. 67–75, 2012.

FREITAS, C. et al. Tagsets and Datasets: Some Experiments Based on Portuguese Language. (A. Villavicencio et al., Eds.)Computational Processing of the Portuguese Language. Anais...Cham: Springer International Publishing, 2018.

FREITAS, C. Linguística Computacional. [s.l.] Parábola Editorial, 2022.

FREITAS, C. et al. Recursos linguísticos para o PLN específico de domínio: o Petrolês. Linguamática, v. 15, n. 2, p. 51–68, 2023.

FREITAS, C.; PARDO, T. A. S. PropBanks e representações semânticas: o que temos, o que queremos e o que podemos. Linguamática, v. 17, n. 2, 2025.

FREITAS, C.; ROCHA, P.; BICK, E. Floresta sintá(c)tica: bigger, thicker and easier. International Conference on Computational Processing of the Portuguese Language. Anais...Springer, b2008.

FREITAS, C.; SANTOS, D. Gender Depiction in Portuguese: Distant reading Brazilian and Portuguese literature. 2nd Annual Conference of Computational Literary Studies. Anais...2023. Disponível em: <https://www.linguateca.pt/Diana/download/FreitasSantos2023-2ndCCLS.pdf>

FREITAS, C.; SOUZA, E. Sujeito oculto às claras: uma abordagem descritivo-computacional / Omitted subjects revealed: a quantitative-descriptive approach. REVISTA DE ESTUDOS DA LINGUAGEM, v. 29, n. 2, p. 1033–1058, 2021.

FREITAS, C.; SOUZA, E. DE. A study on methods for revising dependency treebanks: in search of gold. Language Resources and Evaluation, v. 58, n. 1, p. 11–131, 2024.

FRESCHI, A. C. A avaliação por pares no teletandem institucional integrado: um estudo de caso sobre o feedback linguı́stico nas sessões orais em português. mathesis—[s.l.] Universidade Estadual Paulista (Unesp), 2017.

FRIEDMAN, B. et al. Value sensitive design and information systems. Early engagement and new technologies: Opening up the laboratory, p. 55–95, 2013.

GAGO, P. C. Questões de transcrição em análise da conversa. Veredas-Revista de Estudos Linguı́sticos, v. 6, n. 2, 2002.

GAIZAUSKAS, R. Evaluating Language Processing Applications and Components., 2003. Disponível em: <https://www.linguateca.pt/Repositorio/rgaizauskasPROPOR2003.pdf>

GAMMERMAN, A.; VOVK, V.; VAPNIK, V. Learning by Transduction. : UAI’98.San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 1998.

GAO, Y. et al. Retrieval-Augmented Generation for Large Language Models: A Survey., 2024. Disponível em: <https://arxiv.org/abs/2312.10997>

GARCEZ, P. DE M. A organização da fala-em-interação na sala de aula: controle social, reprodução de conhecimento, construção conjunta de conhecimento. Calidoscópio, v. 4, n. 1, p. 66–80, 2006.

GARCEZ, P. M.; LODER, L. L. Reparo iniciado e levado a cabo pelo outro na conversa cotidiana em português do Brasil. DELTA: Documentação de Estudos em Lingüı́stica Teórica e Aplicada, v. 21, p. 279–312, 2005.

GARCIA, M. et al. Probing for idiomaticity in vector space models. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Anais...Online: Association for Computational Linguistics, abr. 2021. Disponível em: <https://aclanthology.org/2021.eacl-main.310>

GARCIA, M.; GAMALLO, P. An Entity-Centric Coreference Resolution System for Person Entities with Rich Linguistic Information. Proceedings of 25th International Conference on Computational Linguistics. Anais...Dublin, Ireland: 2014. Disponível em: <http://aclweb.org/anthology/C/C14/C14-1070.pdf>

GARDENT, C. et al. The WebNLG Challenge: Generating Text from RDF Data. Proceedings of the 10th International Conference on Natural Language Generation. Anais...: INLG’17.Santiago de Compostela, Spain: Association for Computational Linguistics, 2017. Disponível em: <http://aclweb.org/anthology/W17-3518>

GARGETT, A. et al. The GIVE-2 Corpus of Giving Instructions in Virtual Environments. Proceedings of LREC-2010. Anais...Valletta, Malta: ELRA, 2010.

GATT, A.; BELZ, A. Introducing Shared Tasks to NLG: The TUNA Shared Task Evaluation Challenges. Em: KRAHMER, E.; THEUNE, M. (Eds.). Empirical Methods in Natural Language Generation. Berlin, Heidelberg: Springer-Verlag, 2010. p. 264–293.

GATT, A.; KRAHMER, E. Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation. Journal of Artificial Intelligence Research, v. 61, n. 1, p. 65–170, 2018.

GATT, A.; SLUIS, I. VAN DER; DEEMTER, K. VAN. Evaluating algorithms for the generation of referring expressions using a balanced corpus. Proceedings of ENLG-07. Anais...Schloss Dagstuhl, Germany: Association for Computational Linguistics, 2007.

GAUY, M. M.; FINGER, M. Pretrained audio neural networks for Speech emotion recognition in Portuguese. Proceedings of the Workshop on Automatic Speech Recognition for Spontaneous and Prepared Speech & Speech Emotion Recognition in Portuguese co-located with 15th edition of the International Conference on the Computational Processing of Portuguese (PROPOR 2022). Anais...2022.

GEERAERT, K.; BAAYEN, R. H.; NEWMAN, J. “Spilling the bag” on idiomatic variation. Em: MARKANTONATOU, S. et al. (Eds.). Multiword expressions at length and in depth: Extended papers from the MWE 2017 workshop. Berlin: Language Science Press., 2018. p. 1–33.

GEHRMANN, S. et al. The gem benchmark: Natural language generation, its evaluation and metrics. arXiv preprint arXiv:2102.01672, 2021.

GEY, F. et al. GeoCLEF 2006: the CLEF 2006 Cross-Language Geographic Information Retrieval Track Overview. Em: PETERS, C. et al. (Eds.). Evaluation of Multilingual and Multi-modal Information Retrieval - 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006. Alicante, Spain, September, 2006. Revised Selected papers. Lecture Notes em Computer Science. Berlin / Heidelberg: Springer, 2007. v. 4730p. 852–876.

GIAMPICCOLO, D. et al. Overview of the CLEF 2007 Multilingual Question Answering Track. Em: PETERS, C. et al. (Eds.). Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers. Lecture Notes em Computer Science. Berlin: Springer, 2008. v. 5152p. 200–236.

GILES, H. Communication Accommodation Theory. The International Encyclopedia of Communication Theory and Philosophy, p. 1–7, 2016.

GINZBURG, J. The Interactive Stance. [s.l.] Oxford University Press, 2012.

GINZBURG, J.; FERNÁNDEZ, R. M.; SCHLANGEN, D. Disfluencies as intra-utterance dialogue moves. Semantics and Pragmatics, v. 7, n. 9, p. 64, 2014.

GOLDBERG, A. Constructions at Work: The Nature of Generalization in Language. [s.l.] Oxford University Press, 2005.

GOLDBERG, A. E. Compositionality. Em: RIEMER, N. (Ed.). The Routledge Handbook of Semantics. [s.l.] Routledge, 2015.

GOLDBERG, E.; DRIEDGER, N.; KITTREDGE, R. I. Using Natural-Language Processing to Produce Weather Forecasts. IEEE Expert: Intelligent Systems and Their Applications, p. 45–53, 1994.

GOLUB, G. H.; REINSCH, C. Singular Value Decomposition and Least Squares Solutions. [s.l.] Numer. Math 14, 1970. p. 403–420

GOMES, D. S.; COELHO, O.; MORGADO, C. As implicações da espacialização como categoria analı́tica da conversa na Lı́ngua Brasileira de Sinais e na Lı́ngua Gestual Portuguesa. Sensos-e, v. 7, n. 3, p. 57–69, 2020.

GONÇALO OLIVEIRA, H. Beyond the automatic construction of a lexical ontology for Portuguese: resources developed in the scope of Onto.PT. Proceedings of Workshop on Tools and Resources for Automatically Processing Portuguese and Spanish. Anais...: TorPorEsp.São Carlos, SP, Brasil: BDBComp, 2014. Disponível em: <http://www.lbd.dcc.ufmg.br/colecoes/torporesp/2014/004.pdf>

GONÇALO OLIVEIRA, H. et al. Using Lucene for Developing a Question-Answering Agent in Portuguese. (R. Rodrigues et al., Eds.)8th Symposium on Languages, Applications and Technologies (SLATE 2019). Anais...: Open Access Series em Informatics (OASIcs).Dagstuhl, Germany: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2019. Disponível em: <https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2019.2>

GONÇALO OLIVEIRA, H. et al. A Brief Survey of Textual Dialogue Corpora. Proceedings of the Thirteenth Language Resources and Evaluation Conference. Anais...Marseille, France: European Language Resources Association, jun. 2022. Disponível em: <https://aclanthology.org/2022.lrec-1.135>

GONÇALO OLIVEIRA, H.; GOMES, P. ECO and Onto-PT: a flexible approach for creating a Portuguese Wordnet automatically. Language Resources and Evaluation, v. 48, n. 2, p. 373–393, 2014.

GONÇALVES, M. et al. Avaliação de recursos computacionais para o português. Linguamática, v. 12, n. 2, p. 51–68, 2020.

GONÇALVES, S. C. L. Projeto ALIP (Amostra Linguística do Interior Paulista) e banco de dados Iboruna: 10 anos de contribuição com a descrição do português brasileiro. Estudos Linguísticos (São Paulo. 1978), v. 48, n. 1, p. 276–297, 2019.

GOODFELLOW, I.; BENGIO, Y.; COURVILLE, A. Deep Learning. [s.l.] MIT Press, 2016. v. 1

GOODING, S.; TASLIMIPOOR, S.; KOCHMAR, E. Incorporating Multiword Expressions in Phrase Complexity Estimation. Proceedings of the 1st Workshop on Tools and Resources to Empower People with REAding DIfficulties (READI). Anais...Marseille, France: European Language Resources Association, 2020. Disponível em: <https://aclanthology.org/2020.readi-1.3>

GORMAN, K.; BEDRICK, S. We Need to Talk about Standard Splits. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Anais...Florence, Italy: Association for Computational Linguistics, jul. 2019. Disponível em: <https://aclanthology.org/P19-1267>

GRALIŃSKI, F. et al. Computational Lexicography of Multi-Word Units. How Efficient Can It Be? Proceedings of the 2010 Workshop on Multiword Expressions: from Theory to Applications. Anais...Beijing, China: Coling 2010 Organizing Committee, ago. 2010. Disponível em: <https://aclanthology.org/W10-3702>

GREEN, S.; MARNEFFE, M.-C. DE; MANNING, C. D. Parsing Models for Identifying Multiword Expressions. Computational Linguistics, v. 39, n. 1, p. 195–227, mar. 2013.

GRÉGOIRE, N. DuELME: a Dutch electronic lexicon of multiword expressions. Language Resources and Evaluation, v. 44, p. 23–39, 2010.

GREGOROMICHELAKI, E. et al. Incrementality and intention-recognition in utterance processing. Dialogue & Discourse, v. 2, n. 1, p. 199–233, 2011.

GRIES, S. C. Estatística com R para a Linguística. [s.l.] FALE/ UFMG, 2019.

GRIS, L. R. S. et al. Bringing NURC/SP to digital life: the role of open-source automatic speech recognition models. Anais do XIX Encontro Nacional de Inteligência Artificial e Computacional. Anais...Porto Alegre, RS, Brasil: SBC, 2022. Disponível em: <https://sol.sbc.org.br/index.php/eniac/article/view/22793>

GRIS, L. R. S. et al. Evaluating OpenAI’s Whisper ASR for Punctuation Prediction and Topic Modeling of life histories of the Museum of the Person., 2023. Disponível em: <https://arxiv.org/abs/2305.14580>

GROSS, M. Lexicon - Grammar The Representation of Compound Words. Coling 1986 Volume 1: The 11th International Conference on Computational Linguistics. Anais...1986. Disponível em: <https://aclanthology.org/C86-1001>

GROSZ, B. J.; JOSHI, A. K.; WEINSTEIN, S. Centering: A framework for modelling the local coherence of discourse. IRCS Technical Reports Series, 1995.

GROSZ, B. J.; SIDNER, C. L. Attention, intentions, and the structure of discourse. Computational linguistics, v. 12, n. 3, p. 175–204, 1986.

GROUP, E. E. W. et al. EAGLES Evaluation of Natural Language Processing Systems - Final Report. ISSCO, 1996. Disponível em: <https://www.issco.unige.ch/en/research/projects/eagles/index.html>

GRUBER, T. R. Siri, A Virtual Personal Assistant-Bringing Intelligence to the Interface. Semantic Technologies Conference. Anais...2009.

GUERINO, G.; VALENTIM, N. “Is anybody there?”: Exploring the use and difficulties of Brazilians with Conversational Systems. Anais do XIX Simpósio Brasileiro sobre Fatores Humanos em Sistemas Computacionais. Anais...Porto Alegre, RS, Brasil: SBC, 2020. Disponível em: <https://sol.sbc.org.br/index.php/ihc/article/view/13835>

GULATI, A. et al. Conformer: Convolution-augmented Transformer for Speech Recognition. CoRR, v. abs/2005.08100, 2020.

GUO, Q. et al. P2: A Plan-and-Pretrain Approach for Knowledge Graph-to-Text Generation. Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+). Anais...2020.

GURURANGAN, S. et al. Annotation Artifacts in Natural Language Inference Data. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers). Anais...New Orleans, Louisiana: Association for Computational Linguistics, jun. 2018. Disponível em: <https://aclanthology.org/N18-2017>

GURURANGAN, S. et al. Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Anais...Online: Association for Computational Linguistics, jul. 2020. Disponível em: <https://aclanthology.org/2020.acl-main.740>

HAGÈGE, C.; BAPTISTA, J.; MAMEDE, N. Portuguese Temporal Expressions Recognition: from TE characterization to an effective TER module implementation. The 7th Brazilian Symposium in Information and Human Language Technology (STIL 2009). Anais...São Carlos, Brasil: 2009. Disponível em: <http://www.nilc.icmc.usp.br/til/stil2009_English/Proceedings/stil/Hagege-57697_1.pdf>

HAGEMEIJER, T. et al. The PALMA Corpora of African Varieties of Portuguese. Proceedings of the Thirteenth Language Resources and Evaluation Conference. Anais...Marseille, France: European Language Resources Association, jun. 2022. Disponível em: <https://aclanthology.org/2022.lrec-1.539>

HALL, J. A Probabilistic Part-of-Speech Tagger with Suffix Probabilities. tese de doutorado—[s.l: s.n.].

HALLIDAY, M. A. K.; MATTHIESSEN, C. M. I. M. Construing Experience Through Meaning: A Language Based Approach to Cognition. [s.l.] Continuum, 1999.

HAPKE, H.; HOWARD, C.; LANE, H. Natural Language Processing in Action: Understanding, analyzing, and generating text with Python. [s.l.] Manning, 2019.

HARMAN, D. The Text Retrieval Conferences (TRECs): Providing a Test-Bed for Information Retrieval Systems. Bulletin of the American Society for Information Science, v. 24, n. 4, p. 11–13, 1998.

HARRIS, Z. S. Distributional Structure. Word, v. 10, n. 2-3, p. 146–162, 1954.

HAUSSER, R. The coordinator’s final report on the first Morpholympics. Em: HAUSSER, R. (Ed.). Linguistische Verifikation: Dokumentation zur Ersten Morpholympics 1994. [s.l.] Max Niemeyer Verlag, 1996. p. 167–181.

HAVASI, C.; SPEER, R.; ALONSO, J. ConceptNet 3: a Flexible, Multilingual Semantic Network for Common Sense Knowledge. Recent Advances in Natural Language Processing. Anais...Borovets, Bulgaria: To appear, 2007.

HAVIV, A. et al. Understanding Transformer Memorization Recall Through Idioms. Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics. Anais...Dubrovnik, Croatia: Association for Computational Linguistics, 2023. Disponível em: <https://aclanthology.org/2023.eacl-main.19>

HAYES, P. Expanding the Horizons of Natural Language Interfaces. 18th Annual Meeting of the Association for Computational Linguistics. Anais...Philadelphia, Pennsylvania, USA: Association for Computational Linguistics, jun. 1980. Disponível em: <https://aclanthology.org/P80-1019>

HAYES, P. J.; REDDY, D. R. Steps toward graceful interaction in spoken and written man-machine communication. International Journal of Man-Machine Studies, v. 19, n. 3, p. 231–284, 1983.

HEALEY, P. G.; MILLS, G. J. A Dialogue Experimentation Toolkit. Proceedings of the Annual Meeting of the Cognitive Science Society. Anais...2009. Disponível em: <https://dialoguetoolkit.github.io/chattool/>

HEEMAN, P. A. Dialogue transcription tools - TRAINS Technical Note 94-1. [s.l.] University of Rochester, 1995. Disponível em: <https://dl.acm.org/doi/abs/10.5555/898276>.

HEEMAN, P. A.; HIRST, G. Collaborating on Referring Expressions. Computational Linguistics, v. 21, n. 3, p. 351–382, 1995.

HEIKKILÄ, M. Why you shouldn’t trust AI search engines. Disponível em: <https://www.technologyreview.com/2023/02/14/1068498/why-you-shouldnt-trust-ai-search-engines/>. Acesso em: 9 abr. 2023.

HEIKKILÄ, M. The viral AI avatar app Lensa undressed me—without my consent. Disponível em: < https://www.technologyreview.com/2022/12/12/1064751/the-viral-ai-avatar-app-lensa-undressed-me-without-my-consent/>. Acesso em: 28 ago. 2023.

HEIM, I. File Change Semantics and the Familiarity Theory of Definiteness. Em: Formal Semantics. [s.l.] Wiley-Blackwell, 2008. p. 223–248.

HELDNER, M.; EDLUND, J. Pauses, gaps and overlaps in conversations. Journal of Phonetics, v. 38, n. 4, p. 555–568, 2010.

HENDERSON, P. et al. Ethical challenges in data-driven dialogue systems. Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society. Anais...2018. Disponível em: <https://doi.org/10.1145/3278721.3278777>

HENDRICKX, I. et al. SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations between Pairs of Nominals. Proceedings of the 5th International Workshop on Semantic Evaluation. Anais...2010. Disponível em: <http://www.aclweb.org/anthology/S10-1006>

HENDRYCKS, D. et al. Measuring Massive Multitask Language Understanding. Proceedings of the International Conference on Learning Representations (ICLR). Anais...b2021.

HENDRYCKS, D. et al. Aligning AI With Shared Human Values. Proceedings of the International Conference on Learning Representations (ICLR). Anais...a2021.

HICKE, Y. et al. Assessing the efficacy of large language models in generating accurate teacher responses. arXiv preprint arXiv:2307.04274, 2023.

HILGERT, J. G. A construção do sentido e da compreensão na conversa, mostrada em procedimentos meta-enunciativos. Linha D’Água, v. 25, n. 2, p. 107–129, 2012.

HILGERT, J. G. A emergência da compreensão na conversa, mostrada no trabalho colaborativo de otimização de enunciados. Todas as Letras-Revista de Lı́ngua e Literatura, v. 16, n. 1, 2014.

HIRSCHMAN, L. The evolution of Evaluation: Lessons from the Message Understanding Conferences. Computer Speech and Language, v. 12, n. 4, p. 281–305, 1998.

HIRSCHMAN, L.; THOMPSON, H. S. Overview of Evaluation in Speech and Natural Language Processing. Em: Survey of the State of the Art in Human Language Technology. USA: Cambridge University Press, 1997. p. 409–414.

HORA, N. DA. Coded Bias: linguagem acessível para entender vieses em algoritmos. Disponível em: < https://mittechreview.com.br/coded-bias-linguagem-acessivel-para-entender-vieses-em-algoritmos/>. Acesso em: 7 abr. 2023.

HORA, N. DA. Ética em IA: a pergunta que não estamos fazendo. Disponível em: <https://mittechreview.com.br/etica-em-ia-a-pergunta-que-nao-estamos-fazendo/>. Acesso em: 7 abr. 2023.

HORSMANN, T.; ZESCH, T. Assigning Fine-grained PoS Tags based on High-precision Coarse-grained Tagging. Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers. Anais...Osaka, Japan: The COLING 2016 Organizing Committee, dez. 2016. Disponível em: <https://aclanthology.org/C16-1032>

HOU, Y.; MARKERT, K.; STRUBE, M. A Rule-Based System for Unrestricted Bridging Resolution: Recognizing Bridging Anaphora and Finding Links to Antecedents. Proceedings of the Conference on Empirical Methods in Natural Language Processing. Anais...Doha, Qatar: 2014. Disponível em: <http://aclweb.org/anthology/D/D14/D14-1222.pdf>

HSU, W.-N. et al. Hubert: Self-supervised speech representation learning by masked prediction of hidden units. IEEE/ACM Transactions on Audio, Speech, and Language Processing, v. 29, p. 3451–3460, 2021.

HUANG, J.-T.; HASEGAWA-JOHNSON, M.; SHIH, C. Unsupervised prosodic break detection in Mandarin speech. Proc. Speech Prosody 2008. Anais...2008.

HUANG, X.; ACERO, A.; HON, H. W. Spoken Language Processing: A Guide to Theory, Algorithm, and System Development. [s.l.] Prentice Hall PTR, 2001.

HWANG, A.; HIDEY, C. Confirming the Non-compositionality of Idioms for Sentiment Analysis. Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019). Anais...Florence, Italy: Association for Computational Linguistics, ago. 2019. Disponível em: <https://aclanthology.org/W19-5114>

ILARI, R.; GERALDI, J. W. Semântica. [s.l.] Ética, 1985.

INFOBASE. Inteligência Artificial e a perpetuação do racismo. Disponível em: <https://infobase.com.br/inteligencia-artificial-e-a-perpetuacao-do-racismo/>. Acesso em: 28 ago. 2023.

ISCEN, A. et al. Label Propagation for Deep Semi-Supervised Learning. jun. 2019.

ITO, K. The LJ speech dataset. https://keithito.com/LJ-Speech-Dataset/, 2017.

JACINTHO, F.; PENHA, A. Interfaces conversacionais: Análise de tarefas para Siri e Google Now. Ergodesign & HCI, v. 4, n. 2, p. 72–81, 2016.

JAFARLOU, M.; KUBEK, M. M. Reducing Labeling Costs in Sentiment Analysis via Semi-Supervised Learning. Proceedings of the 2024 8th International Conference on Natural Language Processing and Information Retrieval. Anais...: NLPIR ’24.New York, NY, USA: Association for Computing Machinery, 2025. Disponível em: <https://doi.org/10.1145/3711542.3711570>

JEON, J. H.; LIU, Y. Semi-supervised Learning for Automatic Prosodic Event Detection Using Co-training Algorithm. Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP. Anais...Suntec, Singapore: Association for Computational Linguistics, ago. 2009. Disponível em: <https://aclanthology.org/P09-1061>

JI, Z. et al. Survey of Hallucination in Natural Language Generation. ACM Comput. Surv., v. 55, n. 12, mar. 2023.

JIANG, R.; BANCHS, R. E.; LI, H. Evaluating and Combining Named Entity Recognition Systems. Proceedings of the Sixth Named Entity Workshop, joint with 54th ACL. Anais...2016. Disponível em: <https://www.aclweb.org/anthology/W16-2703.pdf>

JOHNSON, K. Acoustic and Auditory Phonetics. [s.l.] Wiley, 2011.

JOOS, M. Description of language design. Journal of Acoustical Society of America - JASA, v. 22, p. 701–708, 1950.

JOSÉ, M. M. et al. Integrating Question Answering and Text-to-SQL in Portuguese. (V. Pinheiro et al., Eds.)Computational Processing of the Portuguese Language. Anais...Cham: Springer International Publishing, 2022.

JOSHI, M. et al. BERT for Coreference Resolution: Baselines and Analysis. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Anais...Hong Kong, China: Association for Computational Linguistics, nov. 2019. Disponível em: <https://aclanthology.org/D19-1588>

JURAFSKY, D.; MARTIN, J. H. Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. 3rd. ed. USA: Prentice Hall PTR, 2023.

KAHANE, S.; COURTIN, M.; GERDES, K. Multi-word annotation in syntactic treebanks - Propositions for Universal Dependencies. Proceedings of the 16th International Workshop on Treebanks and Linguistic Theories. Anais...Prague, Czech Republic: 2017. Disponível em: <https://aclanthology.org/W17-7622>

KANDO, N. NTCIR and Its Background – Evaluation Workshop on Information Access Technologies and Test Collections. Journal of the Japanese Society for Artificial Intelligence, v. 17, n. 3, p. 296–300, 2002.

KANITZ, A.; FRANK, I. Aprendizagem enquanto produção conjunta de conhecimento: avançando tarefas e alcançando entendimentos satisfatórios na fala-em-interação. Revista Brasileira de Linguı́stica Aplicada, v. 14, p. 111–140, 2014.

KANITZ, A.; LUZ, R. L. Letramento multimodal e construção conjunta de conhecimento na fala-em-interação. Revista Brasileira de Linguı́stica Aplicada, v. 19, p. 603–633, 2019.

KANTAYYA, S. Coded Bias. Disponível em: < https://www.codedbias.com>. Acesso em: 7 abr. 2023.

KARPAS, E. et al. MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning., 2022. Disponível em: <https://arxiv.org/abs/2205.00445>

KATO, A.; SHINDO, H.; MATSUMOTO, Y. Construction of an English Dependency Corpus incorporating Compound Function Words. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16). Anais...Portorož, Slovenia: European Language Resources Association (ELRA), 2016. Disponível em: <https://aclanthology.org/L16-1263>

KENEDY, E.; OTHERO, G. DE Á. Para conhecer sintaxe. São Paulo: Contexto, 2018.

KILGARRIFF, A. I Don’t Believe in Word Senses. Computers and the Humanities, 1997.

KILGARRIFF, A. Thesauruses for Natural Language Processing. Proceedings of Natural Language Processing and Knowledge Engineering. Anais...2003. Disponível em: <https://www.kilgarriff.co.uk/Publications/2003-K-Beijing-thes4NLP.pdf>

KIM, J. et al. Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Search. arXiv preprint arXiv:2005.11129, 2020.

KIM, J.; KONG, J.; SON, J. Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech. International Conference on Machine Learning. Anais...PMLR, 2021.

KIM, S. N. et al. SemEval-2010 Task 5 : Automatic Keyphrase Extraction from Scientific Articles. Proceedings of the 5th International Workshop on Semantic Evaluation. Anais...Uppsala, Sweden: Association for Computational Linguistics, jul. 2010. Disponível em: <https://aclanthology.org/S10-1004>

KING, M. Evaluating Natural Language Processing Systems. Communications of the ACM, v. 39, n. 1, p. 73–79, jan. 1996.

KIPPER, K.; DANG, H. T.; PALMER, M. Class-Based Construction of a Verb Lexicon. Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence. Anais...AAAI Press, 2000.

KIRK, H. et al. Handling and Presenting Harmful Text in NLP Research. Findings of the Association for Computational Linguistics: EMNLP 2022. Anais...Abu Dhabi, United Arab Emirates: Association for Computational Linguistics, dez. 2022. Disponível em: <https://aclanthology.org/2022.findings-emnlp.35>

KIRSTAIN, Y.; RAM, O.; LEVY, O. Coreference Resolution without Span Representations. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). Anais...2021.

KITZINGER, C. Repair. Em: The handbook of conversation analysis. [s.l.] Wiley Online Library, 2012. p. 229–256.

KLATT, D. H. Software for a cascade/parallel formant synthesizer. the Journal of the Acoustical Society of America, v. 67, n. 3, p. 971–995, 1980.

KLIE, J.-C. et al. The INCEpTION Platform: Machine-Assisted and Knowledge-Oriented Interactive Annotation. Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations. Anais...Santa Fe, USA: Association for Computational Linguistics, 2018. Disponível em: <http://tubiblio.ulb.tu-darmstadt.de/106270/>

KOCH, I. G. V. O texto e a construção do sentido. 7. ed. Campinas, SP: Contexto, 2003.

KOCH, I. G. V. Digressão e Relevância Conversacional. Cadernos de Estudos Linguísticos, v. 37, p. 81–91, 2012.

KOCH, I. G. V.; TRAVAGLIA, L. Texto e coerência. 13. ed. [s.l.] Cortez, 2012.

KÖHN, A. Incremental Natural Language Processing: Challenges, Strategies, and Evaluation. Proceedings of the 27th International Conference on Computational Linguistics. Anais...Santa Fe, New Mexico, USA: Association for Computational Linguistics, ago. 2018. Disponível em: <https://aclanthology.org/C18-1253>

KOIZUMI, Y. et al. Miipher: A Robust Speech Restoration Model Integrating Self-Supervised Speech and Text Representations. arXiv preprint arXiv:2303.01664, b2023.

KOIZUMI, Y. et al. LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpus. arXiv preprint arXiv:2305.18802, a2023.

KONRAD, P. G. A busca vs. o resguardo de informações acerca dos crimes em interrogatórios policiais: um olhar sob a perspectiva da fala-em-interação. mathesis—[s.l.] Universidade do Vale do Rio dos Sinos, 2018.

KOPPATZ, M. et al. Automatic generation of factual news headlines in finnish. arXiv preprint arXiv:2212.02170, 2022.

KORKONTZELOS, I. Unsupervised Learning of Multiword Expressions. tese de doutorado—York, UK: University of York, 2011.

KORSKO, P. The narrative shape of two-party complaints in Portuguese: A discourse analytic study. tese de doutorado—[s.l.] Teachers College, Columbia University, 2004.

KOWAL, S.; O’CONNELL, D. C. Transcription as a crucial step of data analysis. The SAGE handbook of qualitative data analysis, p. 64–79, 2014.

KRAHMER, E.; DEEMTER, K. VAN. Computational generation of referring expressions: A survey. Computational Linguistics, v. 38, n. 1, p. 173–218, 2012.

KRAHMER, E.; ERK, S. VAN; VERLEG, A. Graph-Based Generation of Referring Expressions. Computational Linguistics, v. 29, n. 1, p. 53–72, 2003.

KRAHMER, E.; THEUNE, M. Efficient context-sensitive generation of referring expressions. Em: DEEMTER, K. VAN; KIBBLE, R. (Eds.). Information sharing: Reference and presupposition in language generation and interpretation. Stanford, CA: CSLI, 2002. p. 223–264.

KRIPPENDORFF, K. Estimating the Reliability, Systematic Error and Random Error of Interval Data. Educational and Psychological Measurement, v. 30, n. 1, p. 61–70, 1970.

KRUSE, J. S.; BARBOSA, P. A. Alinha-PB: a phonetic aligner for Brazilian Portuguese. Journal of Communication and Information Systems, v. 36, n. 1, p. 192–199, dez. 2021.

KUDO, T. Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Anais...Melbourne, Australia: Association for Computational Linguistics, jul. 2018. Disponível em: <https://aclanthology.org/P18-1007>

KUKICH, K. Design of a Knowledge-based Report Generator. Proceedings of the 21st Annual Meeting on Association for Computational Linguistics. Anais...: ACL’83.Cambridge, Massachusetts: Association for Computational Linguistics, 1983. Disponível em: <https://doi.org/10.3115/981311.981340>

KUMAWAT, D.; JAIN, V. POS Tagging Approaches: A Comparison. International Journal of Computer Applications, v. 118, n. 6, p. 32–38, maio 2015.

KUO, Y. et al. Community-Based Game Design: Experiments on Social Games for Commonsense Data Collection. Proceedings of the ACM SIGKDD Workshop on Human Computation. Anais...: HCOMP ’09.New York, NY, USA: Association for Computing Machinery, 2009. Disponível em: <https://doi.org/10.1145/1600150.1600154>

KYLE, K. K. J. F. S.; JOSE, K. A. C. Y. B.; SOTELO, S. M. Char2wav: End-to-end speech synthesis. International Conference on Learning Representations, workshop. Anais...2017.

LACERDA, A. R. T. DE; AGUIAR, C. S. R. FLOSS FAQ Chatbot Project Reuse: How to Allow Nonexperts to Develop a Chatbot. Proceedings of the 15th International Symposium on Open Collaboration. Anais...: OpenSym ’19.New York, NY, USA: Association for Computing Machinery, 2019. Disponível em: <https://doi.org/10.1145/3306446.3340823>

LAKHOTIA, K. et al. On Generative Spoken Language Modeling from Raw Audio. Transactions of the Association for Computational Linguistics, v. 9, p. 1336–1354, 2021.

LARSSON, S. User-initiated Sub-dialogues in State-of-the-art Dialogue Systems. Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue. Anais...Saarbrücken, Germany: Association for Computational Linguistics, ago. 2017. Disponível em: <https://aclanthology.org/W17-5503>

LAVIE, A.; AGARWAL, A. Meteor: An Automatic Metric for MT Evaluation with High Levels of Correlation with Human Judgments. Proceedings of the Second Workshop on Statistical Machine Translation. Anais...: StatMT’07.Prague, Czech Republic: 2007. Disponível em: <http://dl.acm.org/citation.cfm?id=1626355.1626389>

LEBRET, R.; GRANGIER, D.; AULI, M. Neural Text Generation from Structured Data with Application to the Biography Domain. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. Anais...: EMNLP’16.Austin, Texas: Association for Computational Linguistics, 2016. Disponível em: <http://aclanthology.coli.uni-saarland.de/pdf/D/D16/D16-1128.pdf>

LEE, C. VAN DER et al. Human evaluation of automatically generated text: Current trends and best practice guidelines. Computer Speech & Language, v. 67, p. 101151, 2021.

LEE, C. VAN DER; KRAHMER, E.; WUBBEN, S. PASS: A Dutch data-to-text system for soccer, targeted towards specific audiences. Proceedings of INLG-2017. Anais...Santiago de Compostela, Spain: Association for Computational Linguistics, a2017. Disponível em: <http://aclweb.org/anthology/W17-3513>

LEE, H. et al. Stanford’s multi-pass sieve coreference resolution system at the CoNLL-2011 shared task. Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task. Anais...2011.

LEE, H. et al. Deterministic coreference resolution based on entity-centric, precision-ranked rules. Computational Linguistics, v. 39, n. 4, p. 885–916, 2013.

LEE, K. et al. End-to-end neural coreference resolution. arXiv preprint arXiv:1707.07045, b2017.

LEIDNER, J. L.; PLACHOURAS, V. Ethical by Design: Ethics Best Practices for Natural Language Processing. Proceedings of the First ACL Workshop on Ethics in Natural Language Processing. Anais...Valencia, Spain: Association for Computational Linguistics, abr. 2017. Disponível em: <https://aclanthology.org/W17-1604>

LENAT, D. B.; GUHA, R. V. Building large knowledge-based systems: representation and inference in the Cyc project. [s.l.] Addison-Wesley, 1989.

LEONARDELLI, E. et al. Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators’ Disagreement. (M.-F. Moens et al., Eds.)Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Anais...Online; Punta Cana, Dominican Republic: Association for Computational Linguistics, nov. 2021. Disponível em: <https://aclanthology.org/2021.emnlp-main.822/>

LEVELT, W. J. Speaking: From intention to articulation. [s.l.] MIT press, 1993.

LEVINSON, S. C. Speech Acts. Em: The Oxford Handbook of Pragmatics. [s.l.] Oxford University Press, 2017.

LEWIS, D. Scorekeeping in a language game. Em: Semantics from different points of view. [s.l.] Springer, 1979. p. 172–187.

LEWIS, M. et al. BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension. (D. Jurafsky et al., Eds.)Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020. Anais...Association for Computational Linguistics, 2020. Disponível em: <https://doi.org/10.18653/v1/2020.acl-main.703>

LGPD. Lei Geral de Proteção de Dados Pessoais (LGPD). Disponível em: <https://www.planalto.gov.br/ccivil_03/_ato2015-2018/2018/lei/l13709.htm>. Acesso em: 9 abr. 2023.

LI, J. et al. Molweni: A challenge multiparty dialogues-based machine reading comprehension dataset with discourse structure. arXiv preprint arXiv:2004.05080, 2020.

LI, S. et al. Defining a New NLP Playground. (H. Bouamor, J. Pino, K. Bali, Eds.)Findings of the Association for Computational Linguistics: EMNLP 2023. Anais...Singapore: Association for Computational Linguistics, dez. 2023. Disponível em: <https://aclanthology.org/2023.findings-emnlp.799>

LI, X.; ROTH, D. Learning question classifiers. COLING 2002: The 19th International Conference on Computational Linguistics. Anais...2002.

LIESENFELD, A.; LOPEZ, A.; DINGEMANSE, M. The timing bottleneck: Why timing and overlap are mission-critical for conversational user interfaces, speech recognition and dialogue systems. Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue. Anais...Prague, Czechia: Association for Computational Linguistics, set. 2023. Disponível em: <https://aclanthology.org/2023.sigdial-1.45>

LIN, C.-H. et al. Rich prosodic information exploration on spontaneous Mandarin speech. 2016 10th International Symposium on Chinese Spoken Language Processing (ISCSLP). Anais...Tianjin: 2016.

LIN, C.-H. et al. Hierarchical prosody modeling for Mandarin spontaneous speech. The Journal of the Acoustical Society of America, v. 145, n. 4, p. 2576–2596, 2019.

LIN, C.-Y. ROUGE: A Package for Automatic Evaluation of Summaries. Text Summarization Branches Out. Anais...Barcelona, Spain: Association for Computational Linguistics, jul. 2004. Disponível em: <https://aclanthology.org/W04-1013>

LIN, D. Automatic Identification of Non-compositional Phrases. Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics. Anais...College Park, Maryland, USA: Association for Computational Linguistics, jun. 1999. Disponível em: <https://aclanthology.org/P99-1041>

LINARDATOS, P.; PAPASTEFANOPOULOS, V.; KOTSIANTIS, S. Explainable AI: A Review of Machine Learning Interpretability Methods. Entropy, v. 23, n. 1, 2021.

LIPTON, Z. C.; STEINHARDT, J. Troubling Trends in Machine Learning Scholarship: Some ML papers suffer from flaws that could mislead the public and stymie future research. Queue, v. 17, n. 1, p. 45–77, 2019.

LITMAN, D. J.; ALLEN, J. F. A plan recognition model for subdialogues in conversations. Cognitive science, v. 11, n. 2, p. 163–200, 1987.

LIU, C.-W. et al. How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. Anais...Austin, Texas: Association for Computational Linguistics, nov. 2016. Disponível em: <https://aclanthology.org/D16-1230>

LIU, H.; SINGH, P. Commonsense Reasoning in and Over Natural Language. (M. Gh. Negoita, R. J. Howlett, L. C. Jain, Eds.)Knowledge-Based Intelligent Information and Engineering Systems. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2004.

LIU, N. F. et al. Lexical Semantic Recognition. Proceedings of the 17th Workshop on Multiword Expressions (MWE 2021). Anais...Online: Association for Computational Linguistics, 2021. Disponível em: <https://aclanthology.org/2021.mwe-1.6>

LODER, L. L.; GONZALEZ, P. C.; GARCEZ, P. M. Reparo em terceira posição e intersubjetividade na fala-em-interação em português brasileiro. Veredas-Revista de Estudos Linguı́sticos, v. 6, n. 2, 2002.

LOPE, J.; GRAÑA, M. An ongoing review of speech emotion recognition. Neurocomputing, 2023.

LOPES, L. et al. PortiLexicon-UD: a Portuguese Lexical Resource according to Universal Dependencies Model. Proceedings of the Language Resources and Evaluation Conference. Anais...Marseille, France: European Language Resources Association, jun. 2022. Disponível em: <https://aclanthology.org/2022.lrec-1.715>

LOPES, L. et al. Disambiguation of Universal Dependencies Part-of-Speech Tags of Closed Class Words in Portuguese. (A. Britto, K. V. Delgado, Eds.)Proceedings of the 12th Brazilian Conference on Intelligent Systems (BRACIS). Anais...2023.

LOPES, L.; PARDO, T. Towards Portparser - a highly accurate parsing system for Brazilian Portuguese following the Universal Dependencies framework. (P. Gamallo et al., Eds.)Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1. Anais...Santiago de Compostela, Galicia/Spain: Association for Computational Lingustics, mar. 2024. Disponível em: <https://aclanthology.org/2024.propor-1.41>

LOSNEGAARD, G. S. et al. PARSEME Survey on MWE Resources. (N. C. (Conference Chair) et al., Eds.)Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). Anais...Paris, France: European Language Resources Association (ELRA), 2016.

LUCY, L.; BAMMAN, D. Gender and Representation Bias in GPT-3 Generated Stories. Proceedings of the Third Workshop on Narrative Understanding. Anais...Virtual: Association for Computational Linguistics, jun. 2021. Disponível em: <https://aclanthology.org/2021.nuse-1.5>

LUDUSAN, B.; SYNNAEVE, G.; DUPOUX, E. Prosodic boundary information helps unsupervised word segmentation. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Anais...2015.

LUO, X. On Coreference Resolution Performance Metrics. Proceedings of the Conference on Empirical Methods in Natural Language Processing. Anais...Vancouver, Canada: 2005.

LYONS, J. Semantics: Volume 2. [s.l.] Cambridge university press, 1977. v. 2

MADUREIRA, B. Flamingos and Hedgehogs in the Croquet-Ground: Teaching Evaluation of NLP Systems for Undergraduate Students. Proceedings of the Fifth Workshop on Teaching NLP. Anais...Online: Association for Computational Linguistics, jun. 2021. Disponível em: <https://aclanthology.org/2021.teachingnlp-1.14>

MADUREIRA, B.; ÇELIKKOL, P.; SCHLANGEN, D. Revising with a Backward Glance: Regressions and Skips during Reading as Cognitive Signals for Revision Policies in Incremental Processing. (J. Jiang, D. Reitter, S. Deng, Eds.)Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL). Anais...Singapore: Association for Computational Linguistics, dez. a2023. Disponível em: <https://aclanthology.org/2023.conll-1.22>

MADUREIRA, B.; KAHARDIPRAJA, P.; SCHLANGEN, D. The Road to Quality is Paved with Good Revisions: A Detailed Evaluation Methodology for Revision Policies in Incremental Sequence Labelling. Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue. Anais...Prague, Czechia: Association for Computational Linguistics, set. b2023. Disponível em: <https://aclanthology.org/2023.sigdial-1.14>

MADUREIRA, B.; LASOTA, L. Das Inquietudes em Tecnologias de Linguagem. Em: Novas Tecnologias. [s.l.] Editora Casa do Direito, 2023.

MADUREIRA, B.; SCHLANGEN, D. Incremental Processing in the Age of Non-Incremental Encoders: An Empirical Assessment of Bidirectional Models for Incremental NLU. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Anais...Online: Association for Computational Linguistics, nov. 2020. Disponível em: <https://aclanthology.org/2020.emnlp-main.26>

MAGNINI, B. et al. Overview of the CLEF 2006 Multilingual Question Answering Track. Em: PETERS, C. et al. (Eds.). Evaluation of Multilingual and Multi-modal Information Retrieval - 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006. Alicante, Spain, September, 2006. Revised Selected papers. Lecture Notes em Computer Science. Berlin / Heidelberg: Springer, 2007. v. 4730p. 223–256.

MAHAJAN, K.; SHAIKH, S. On the Need for Thoughtful Data Collection for Multi-Party Dialogue: A Survey of Available Corpora and Collection Methods. Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue. Anais...Singapore; Online: Association for Computational Linguistics, jul. 2021. Disponível em: <https://aclanthology.org/2021.sigdial-1.36>

MALINGAN, N. Attention Mechanism in Deep Learning., 2024. Disponível em: <https://www.scaler.com/topics/deep-learning/attention-mechanism-deep-learning/>

MANN, W. C.; THOMPSON, S. A. Rhetorical structure theory: Toward a functional theory of text organization. Text-interdisciplinary Journal for the Study of Discourse, v. 8, n. 3, p. 243–281, 1988.

MANNING, C. D.; SCHÜTZE, H. Foundations of statistical natural language processing. Cambridge, USA: mitpress, 1999.

MARCACINI, R. M. et al. Cross-domain aspect extraction for sentiment analysis: A transductive learning approach. Decision Support Systems, v. 114, p. 70–80, 2018.

MARCACINI, R. M.; CANDIDO JUNIOR, A.; CASANOVA, E. Overview of the Automatic Speech Recognition for Spontaneous and Prepared Speech & Speech Emotion Recognition in Portuguese (SE&R) Shared-tasks at PROPOR 2022. Proceedings of the Workshop on Automatic Speech Recognition for Spontaneous and Prepared Speech & Speech Emotion Recognition in Portuguese co-located with 15th edition of the International Conference on the Computational Processing of Portuguese (PROPOR 2022). Anais...2022.

MARCHAL, M. et al. Establishing Annotation Quality in Multi-label Annotations. (N. Calzolari et al., Eds.)Proceedings of the 29th International Conference on Computational Linguistics. Anais...Gyeongju, Republic of Korea: International Committee on Computational Linguistics, out. 2022. Disponível em: <https://aclanthology.org/2022.coling-1.322>

MARCU, D. From local to global coherence: A bottom-up approach to text planning. AAAI/IAAI. Anais...Citeseer, 1997.

MARCU, D.; CARLSON, L.; WATANABE, M. The automatic translation of discourse structures. 1st Meeting of the North American Chapter of the Association for Computational Linguistics. Anais...2000.

MARCUSCHI, L. A. Atos de referenciação na interação face a face. Cadernos de Estudos Linguı́sticos, v. 41, p. 37–54, 2001.

MAREGA, L. M. P.; JUNG, N. M. A sobreposição de falas na conversa cotidiana: disputa pela palavra? Revista Veredas, v. 15, n. 1, 2011.

MARKANTONATOU, S. et al. IDION: A database for Modern Greek multiword expressions. Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019). Anais...Florence, Italy: Association for Computational Linguistics, ago. 2019. Disponível em: <https://aclanthology.org/W19-5115>

MARKANTONATOU, S. et al. PMWE conventions for examples containing multiword expressions., 2021. Disponível em: <https://gitlab.com/parseme/pmwe/-/raw/master/Conventions-for-MWE-examples/PMWE_series_conventions_for_multilingual_examples.pdf>

MARNEFFE, M.-C. DE et al. Universal Dependencies. Computational Linguistics, v. 47, n. 2, p. 255–308, jun. 2021.

MARSLEN-WILSON, W. Linguistic structure and speech shadowing at very short latencies. Nature, v. 244, n. 5417, p. 522–523, 1973.

MARTINS, E. J. Enunciação e diálogo. tese de doutorado—[s.l.] Universidade Estadual de Campinas, Instituto de Estudos da Linguagem, Campinas, SP, 1987.

MARTINS, H. Sobre a estabilidade do significado em Wittgenstein. Veredas, v. 4, n. 2, p. 19–42, 2000.

MARTINS, H. Três Caminhos na Filosofia da Linguagem. Em: Introdução à Linguística. Volume III. [s.l.] Editora Cortez, 2004.

MARTINS, R.; NUNES, M. DAS G. V.; HASEGAWA, R. Curupira: A Functional Parser for Brazilian Portuguese. (N. J. Mamede et al., Eds.)Computational Processing of the Portuguese Language. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2003.

MARTSCHAT, S.; STRUBE, M. Latent Structures for Coreference Resolution. Transactions of the Association for Computational Linguistics, v. 3, p. 405–418, 2015.

MATOS, V. B. et al. Coordination within Conversational Agents with Multiple Sources. Anais do XX Encontro Nacional de Inteligência Artificial e Computacional. Anais...SBC, 2023. Disponível em: <https://doi.org/10.5753/eniac.2023.234533>

MATTOS, L. DE et al. Contribuições para o desenvolvimento de Agentes Pedagógicos Conversacionais e sua integração a Ambientes Virtuais de Aprendizagem. Anais do XXXIII Simpósio Brasileiro de Informática na Educação. Anais...SBC, 2022. Disponível em: <https://doi.org/10.5753/sbie.2022.225088 >

MAZIERO, E. G. et al. A base de dados lexical e a interface web do TeP 2.0: thesaurus eletrônico para o Português do Brasil. Proceedings of the XIV Brazilian Symposium on Multimedia and the Web. Anais...Salvador, Brazil: 2008.

MAZIERO, E. G. Análise retórica com base em grande quantidade de dados. tese de doutorado—[s.l.] Universidade de São Paulo, 2016.

MAZIERO, E. G.; HIRST, G.; PARDO, T. A. S. Adaptation of discourse parsing models for the Portuguese language. 2015 Brazilian Conference on Intelligent Systems (BRACIS). Anais...IEEE, 2015.

MAZIERO, E. G.; JORGE, M. L. DEL R. C.; PARDO, T. A. S. Identifying Multidocument Relations. NLPCS, v. 7, p. 60–69, 2010.

MAZIERO, E. G.; PARDO, T. A. S. Automatic Identification of Multi-document Relations. Proceedings of the PROPOR 2012 PhD and MSc/MA Dissertation Contest, p. 1–8, 2012.

MAZUMDER, M. et al. Multilingual spoken words corpus. Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2). Anais...2021.

MCCRAE, J. P. et al. English WordNet 2019 – An Open-Source WordNet for English. Proceedings of the 10th Global Wordnet Conference. Anais...Wroclaw, Poland: Global Wordnet Association, jul. 2019. Disponível em: <https://aclanthology.org/2019.gwc-1.31>

MCDONALD, R. et al. Universal Dependency Annotation for Multilingual Parsing. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Anais...Sofia, Bulgaria: Association for Computational Linguistics, ago. 2013. Disponível em: <https://aclanthology.org/P13-2017>

MCGUIRE, J. et al. The reputational and ethical consequences of deceptive chatbot use. Scientific Reports, v. 13, n. 1, 2023.

MEER, M. VAN DER et al. Annotator-Centric Active Learning for Subjective NLP Tasks. (Y. Al-Onaizan, M. Bansal, Y.-N. Chen, Eds.)Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Anais...Miami, Florida, USA: Association for Computational Linguistics, nov. 2024. Disponível em: <https://aclanthology.org/2024.emnlp-main.1031/>

MEI, H.; BANSAL, M.; WALTER, M. R. What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment. Proceedings of NAACL-2016. Anais...: HLT-NAACL’16.San Diego, California: Association for Computational Linguistics, 2016. Disponível em: <http://aclanthology.coli.uni-saarland.de/pdf/N/N16/N16-1086.pdf>

MEL’ČUK, I. General Phraseology: Theory and Practice. Amsterdam/Philadelphia: John Benjamins, 2023. v. 36

MEL’ČUK, I.; CLAS, A.; POLGUÈRE, A. Introduction à la lexicologie explicative et combinatoire. Louvain la Neuve, Belgium: Editions Duculot, 1995.

MEL’ČUK, I.; POLGUÈRE, A. A Formal Lexicon In The Meaning-Text Theory Or (How To Do Lexica With Words). cl, v. 13, n. 3-4, p. 261–275, 1987.

MELLO, H.; RASO, T.; ALMEIDA FERRARI, L. DE. C-ORAL–Brasil II: Corpus de referência do português brasileiro falado informal., no prelono prelo.

MELO, G. DE; WEIKUM, G. Towards a universal wordnet by learning from combined evidence. Proceedings of the 18th ACM conference on Information and knowledge management. Anais...2009.

MENDES, R. B.; OUSHIRO, L. Mapping Paulistano Portuguese: the SP2010 Project. Proceedings of the VIIth GSCP International Conference: Speech and Corpora. Anais...Firenze, Italy: Fizenze University Press, 2012.

MIKOLOV, T. et al. Efficient Estimation of Word Representations in Vector Space., a2013. Disponível em: <https://arxiv.org/abs/1301.3781>

MIKOLOV, T. et al. Distributed Representations of Words and Phrases and their Compositionality. (C. J. Burges et al., Eds.)Advances in Neural Information Processing Systems. Anais...Curran Associates, Inc., b2013. Disponível em: <https://proceedings.neurips.cc/paper_files/paper/2013/file/9aa42b31882ec039965f3c4923ce901b-Paper.pdf>

MINSKY, M. A framework for representing knowledge. The psychology of computer vision, 1975.

MITCHELL, M. et al. Model cards for model reporting. Proceedings of the conference on fairness, accountability, and transparency. Anais...2019.

MITKOV, R. The Oxford handbook of Computational Linguistics. [s.l.] Oxford University Press, 2003.

MITKOV, R. 21 Discourse Processing. The handbook of computational linguistics and natural language processing, p. 599, 2010.

MOL, L. et al. The communicative import of gestures: Evidence from a comparative analysis of human–human and human–machine interactions. Gesture, v. 9, n. 1, p. 97–126, 2009.

MONTI, J. et al. (EDS.). Proceedings of The 3rd Workshop on Multi-word Units in Machine Translation and Translation Technology (MUMTTT 2017). Geneva, Switzerland: Editions Tradulex, 2017.

MOORE, R. K. Spoken language processing: Piecing together the puzzle. Speech Communication, v. 49, n. 5, p. 418–435, 2007.

MORAES GARCEZ, P. DE; STEIN, F. Organização da fala-em-interação: o dispositivo para o gerenciamento de fala sobreposta na conversa cotidiana em dados de português brasileiro. Revista de Estudos da Linguagem, v. 23, n. 1, p. 159–194, 2015.

MORETTI, F. Distant Reading. [s.l.] Verso, 2013.

MOTA, C. et al. É tempo de avaliar o tempo. Em: MOTA, C.; SANTOS, D. (Eds.). Desafios na avaliação conjunta do reconhecimento de entidades mencionadas. [s.l.] Linguateca, 2008. p. 55–75.

MOTA, C. et al. Págico: Evaluating Wikipedia-based information retrieval in Portuguese. (N. Calzolari et al., Eds.)Proceedings of the Eigth International Conference on Language Resources and Evaluation (LREC’12). Anais...Istambul: 2012. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2012/pdf/590_Paper.pdf>

MULLER, P. et al. Manuel d’annotation en relations de discours du projet annodis., 2012.

MUNIZ, M. C. M. A construção de recursos linguístico-computacionais para o português do Brasil: o projeto Unitex-PB. mathesis—[s.l.] Instituto de Ciências Matemáticas e de Computação - Universidade de São Paulo - ICMC/USP, 2004.

MURTARELLI, G.; GREGORY, A.; ROMENTI, S. A conversation-based perspective for shaping ethical human–machine interactions: The particular challenge of chatbots. Journal of Business Research, v. 129, p. 927–935, 2021.

MUSGRAVE, K.; BELONGIE, S.; LIM, S.-N. A metric learning reality check. Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXV 16. Anais...Springer, 2020. Disponível em: <https://doi.org/10.1007/978-3-030-58595-2_41>

NAMIUTI, C. O Corpus Anotado do Português Histórico: um avanço para as pesquisas em Linguística Histórica do Português. Revista Virtual de Estudos da Linguagem, v. 2, p. 1–9, ago. 2004.

NASCIMENTO, M. F. B. DO; GONÇALVES, J. B. Corpus de Referência do Português Contemporâneo (CRPC) - desenvolvimento e aplicações. Actas do XI Encontro Nacional da Associação Portuguesa de Lingüı́stica, v. 1, p. 143–150, 1996.

NAVIGLI, R.; PONZETTO, S. P. BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artificial intelligence, v. 193, p. 217–250, 2012.

NEEDHAM, M.; HODLER, A. E. Graph Algorithms: Practical Examples in Apache Spark and Neo4j. [s.l.] O’Reilly Media, 2019.

NETO, J. P. et al. Design of a multimodal input interface for a dialogue system. Computational Processing of the Portuguese Language: 7th International Workshop, PROPOR 2006, Itatiaia, Brazil, May 13-17, 2006. Proceedings 7. Anais...Springer, 2006. Disponível em: <https://doi.org/10.1007/11751984_18>

NEVES, M. H. DE M. Texto e gramática. [s.l.] Contexto, 2013.

NEWELL, A. A tutorial on speech understanding systems. Speech recognition, p. 4–54, 1975.

NG, V.; CARDIE, C. Improving machine learning approaches to coreference resolution. Proceedings of the 40th Annual Meeting on Association for Computational Linguistics. Anais...Association for Computational Linguistics, 2002.

NIVRE, J. et al. The CoNLL 2007 Shared Task on Dependency Parsing. Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL). Anais...Prague, Czech Republic: Association for Computational Linguistics, jun. 2007. Disponível em: <https://aclanthology.org/D07-1096>

NIVRE, J.; FANG, C.-T. Universal Dependency Evaluation. (M.-C. de Marneffe, J. Nivre, S. Schuster, Eds.)Proceedings of the NoDaLiDa 2017 Workshop on Universal Dependencies (UDW 2017). Anais...Gothenburg, Sweden: Association for Computational Linguistics, 2017. Disponível em: <https://aclanthology.org/W17-0411>

NIVRE, J.; NILSSON, J. Multiword units in syntactic parsing. Proceedings of Methodologies and Evaluation of Multiword Units in Real-World Applications (MEMURA), 2004.

NOORALAHZADEH, F.; ØVRELID, L. Syntactic Dependency Representations in Neural Relation Classification. Proceedings of the Workshop on the Relevance of Linguistic Structure in Neural Architectures for NLP. Anais...Melbourne, Australia: Association for Computational Linguistics, jul. 2018. Disponível em: <https://aclanthology.org/W18-2907>

NOVIKOVA, J. et al. Why We Need New Evaluation Metrics for NLG. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Anais...: EMNLP’17.Copenhagen, Denmark: Association for Computational Linguistics, 2017. Disponível em: <http://aclweb.org/anthology/D17-1237>

NOZAKI, J. et al. End-to-end Speech-to-Punctuated-Text Recognition. Proc. Interspeech 2022. Anais...2022.

NUNES, A. S. A coconstrução do conhecimento através de jogos de linguagem em uma aula de língua portuguesa: um estudo das estratégias de leitura a partir da análise dos enquadres interacionais. mathesis—[s.l.] Programa de Pós-Graduação em Letras, Mestrado Profissional (PROFLETRAS); Universidade do Estado do Rio de Janeiro, 2016.

NUNES, E. G. Os marcadores conversacionais na constituição do texto falado. Verbum. Cadernos de Pós-Graduação. ISSN 2316-3267, v. 6, n. 2, p. 120–125, 2017.

NUNES, P. LEVANTAMENTO REVELA QUE 90,5% DOS PRESOS POR MONITORAMENTO FACIAL NO BRASIL SÃO NEGROS. Disponível em: < https://www.intercept.com.br/2019/11/21/presos-monitoramento-facial-brasil-negros/>. Acesso em: 28 ago. 2023.

O’NEIL, C. Algoritmos de Destruição em Massa. [s.l.] Editora Rua do Sabão, 2021.

OECD. The OECD Framework for the Classification of AI systems. Disponível em: < https://wp.oecd.ai/app/uploads/2022/02/Classification-2-pager-1.pdf>. Acesso em: 28 ago. 2023.

OECD. OECD Employment Outlook 2023. [s.l: s.n.]. p. 267

OLIVEIRA, F. S. et al. CML-TTS: A Multilingual Dataset for Speech Synthesis in Low-Resource Languages. International Conference on Text, Speech, and Dialogue. Anais...Springer, 2023.

OLIVEIRA, L. E. S. E. et al. Experiments on Portuguese Clinical Question Answering. (A. Britto, K. Valdivia Delgado, Eds.)Intelligent Systems. Anais...Cham: Springer International Publishing, 2021.

OLIVEIRA, L. F. A. DE et al. Challenges In Annotating A Treebank Of Clinical Narratives In Brazilian Portuguese. Computational Processing of the Portuguese Language: 15th International Conference, PROPOR 2022, Fortaleza, Brazil, March 21–23, 2022, Proceedings. Anais...Berlin, Heidelberg: Springer-Verlag, 2022. Disponível em: <https://doi.org/10.1007/978-3-030-98305-5_9>

OLIVEIRA, L. M. DE; DIAS, J. G. O autorreparo como estratégia adaptativa na fala em interação de um afásico. Linguagem em (Dis) curso, v. 18, p. 49–68, 2018.

OLIVEIRA, M. R. DE et al. Repetição em diálogos: análise funcional da conversação. Série Ensaios, v. 9, 1998.

OLIVEIRA, M. R. DE. Manual de Linguística. Em: MARTELOTTA, M. E. (Ed.). São Paulo: Contexto, 2008. p. 193–204.

OLIVER, A. et al. Realistic evaluation of deep semi-supervised learning algorithms. Proceedings of the 32nd International Conference on Neural Information Processing Systems. Anais...: NIPS’18.Red Hook, NY, USA: Curran Associates Inc., 2018.

OLIVIERA JR., M. NURC Digital: um protocolo para a digitalização, anotação, arquivamento e disseminação do material do Projeto da Norma Urbana Linguística Culta (NURC). CHIMERA: Revista de Corpus de Lenguas Romances y Estudios Lingüísticos, v. 3, n. 2, p. 149–174, set. 2016.

OPENAI. ChatGPT: OpenA’s conversational AI model. Disponível em: <https://openai.com/blog/chatgpt/>. Acesso em: 7 abr. 2023.

ORENGO, V. M.; HUYCK, C. A Stemming Algorithmm for the Portuguese Language. Proceedings Eighth Symposium on String Processing and Information Retrieval. Anais...IEEE Computer Society, 2001.

OSBORNE, D. M. The realization of speech acts of refusals of an invitation among Brazilian friends. Revista de estudos da linguagem, v. 18, n. 2, p. 61–85, 2010.

OSBORNE, T.; GERDES, K. The status of function words in dependency grammar: A critique of Universal Dependencies (UD). Glossa: a journal of general linguistics (2016-2021), jan. 2019.

OSGOOD, C. E.; SUCI, G. J.; TENENBAUM, P. H. The Measurement of meaning. Urbana: University of Illinois Press, 1957.

OSTENDORF, M.; PRICE, P.; SHATTUCK-HUFNAGEL, S. The Boston University Radio news corpus., 1995. Disponível em: <https://doi.org/10.35111/Z7XK-Z229>

OSTERMANN, A. C.; ANDRADE, D. N. P.; FREZZA, M. A prosódia como componente de formação e de atribuição de sentido a ações na fala-em-interação: o caso de formulações no tribunal. DELTA: Documentação de Estudos em Lingüı́stica Teórica e Aplicada, v. 32, p. 481–513, 2016.

OUSHIRO, L. Wh-interrogatives in Brazilian Portuguese: the influence of common ground. University of Pennsylvania Working Papers in Linguistics, v. 17, n. 2, p. 17, 2011.

OUSHIRO, L.; MENDES, R. B. A Variação em interrogativas de constituinte no fluxo conversacional. Signum: Estudos da Linguagem, v. 15, n. 3, p. 273–292, 2012.

OUYANG, L. et al. Training language models to follow instructions with human feedback. (A. H. Oh et al., Eds.)Advances in Neural Information Processing Systems. Anais...2022. Disponível em: <https://openreview.net/forum?id=TG8KACxEON>

OVCHINNIKOVA, E. Integration of World Knowledge for Natural Language Understanding. [s.l.] Atlantis Press, 2012.

ÖZSEVEN, T. Investigation of the effect of spectrogram images and different texture analysis methods on speech emotion recognition. Applied Acoustics, v. 142, p. 70–77, 2018.

PĂIŞ, V.; TUFIŞ, D. Capitalization and punctuation restoration: a survey. Artificial Intelligence Review, v. 55, p. 1681--1722, 2022.

PALMER, M.; FININ, T.; WALTER, S. M. Workshop on the Evaluation of Natural Language Processing Systems. [s.l.] Air Force Systems Command; Rome Air Development Center, 1988. Disponível em: <https://ebiquity.umbc.edu/paper/html/id/1074>.

PALMER, M.; GILDEA, D.; KINGSBURY, P. The Proposition Bank: An Annotated Corpus of Semantic Roles. Computational Linguistics, 31: 1. Anais...The MIT PressJournals, 2005.

PAPINENI, K. et al. BLEU: A Method for Automatic Evaluation of Machine Translation. Proceedings of the 40th Annual Meeting on Association for Computational Linguistics. Anais...: ACL ’02.USA: Association for Computational Linguistics, 2002. Disponível em: <https://doi.org/10.3115/1073083.1073135>

PARABONI, I.; GALINDO, M.; IACOVELLI, D. Stars2: a corpus of object descriptions in a visual domain. Language Resources and Evaluation, v. 51, n. 2, p. 439–462, 2017.

PARDO, T. et al. Porttinari - a Large Multi-genre Treebank for Brazilian Portuguese. Anais do XIII Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana. Anais...Porto Alegre, RS, Brasil: SBC, 2021. Disponível em: <https://sol.sbc.org.br/index.php/stil/article/view/17778>

PARDO, T. A. S. Métodos para análise discursiva automática. tese de doutorado—[s.l.] Universidade de São Paulo, 2005.

PARK, D. S. et al. SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition. Interspeech 2019. Anais...ISCA, set. 2019. Disponível em: <https://doi.org/10.21437%2Finterspeech.2019-2680>

PARMAR, M. et al. Don’t Blame the Annotator: Bias Already Starts in the Annotation Instructions. Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics. Anais...Dubrovnik, Croatia: Association for Computational Linguistics, 2023. Disponível em: <https://aclanthology.org/2023.eacl-main.130>

PAROUBEK, P.; CHAUDIRON, S.; HIRSCHMAN, L. Principles of Evaluation in Natural Language Processing. Revue TAL, v. 48, n. 1, p. 7–31, 2007.

PARRA ESCARTÍN, C. et al. Ethical Considerations in NLP Shared Tasks. Proceedings of the First ACL Workshop on Ethics in Natural Language Processing. Anais...Valencia, Spain: Association for Computational Linguistics, abr. 2017. Disponível em: <https://aclanthology.org/W17-1608>

PARRA ESCARTÍN, C.; NEVADO LLOPIS, A.; SÁNCHEZ MARTÍNEZ, E. Spanish multiword expressions: Looking for a taxonomy. Em: Multiword expressions: Insights from a multi-lingual perspective. [s.l.] Language Science Press, 2018. p. 271–323.

PASCHOAL, A. F. et al. Pirá: A bilingual Portuguese-English dataset for question-answering about the ocean. Proceedings of the 30th ACM International Conference on Information & Knowledge Management. Anais...2021. Disponível em: <https://doi.org/10.1145/3459637.3482012>

PASCHOAL, L. N. et al. Towards a Conversational Agent to Support the Software Testing Education. Proceedings of the XXXIII Brazilian Symposium on Software Engineering. Anais...: SBES ’19.New York, NY, USA: Association for Computing Machinery, 2019. Disponível em: <https://doi.org/10.1145/3350768.3352456>

PASQUER, C. et al. Verbal Multiword Expression Identification: Do We Need a Sledgehammer to Crack a Nut? Proceedings of the 28th International Conference on Computational Linguistics. Anais...Barcelona, Spain (Online): International Committee on Computational Linguistics, dez. 2020.

PAULLADA, A. et al. Data and its (dis) contents: A survey of dataset development and use in machine learning research. Patterns, v. 2, n. 11, 2021.

PENNINGTON, J.; SOCHER, R.; MANNING, C. GloVe: Global Vectors for Word Representation. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Anais...Doha, Qatar: Association for Computational Linguistics, out. 2014. Disponível em: <https://aclanthology.org/D14-1162>

PEREIRA, A. et al. Systematic review of question answering over knowledge bases. IET Software, v. 16, n. 1, p. 1–13, 2022.

PEREZ-BELTRACHINI, L. et al. Content selection as semantic-based ontology exploration. (C. Gardent, A. Gangemi, Eds.)Proceedings of the 2nd International Workshop on Natural Language Generation and the Semantic Web (WebNLG 2016). Anais...Edinburgh, Scotland: Association for Computational Linguistics, set. 2016. Disponível em: <https://aclanthology.org/W16-3508>

PERRAULT, C. R.; ALLEN, J. F. Speech Acts as a Basis for Understanding Dialogue Coherence. Theoretical Issues in Natural Language Processing-2. Anais...1978. Disponível em: <https://aclanthology.org/T78-1017>

PERRIGO, B. Disponível em: <https://time.com/6247678/openai-chatgpt-kenya-workers/>. Acesso em: 9 abr. 2023.

PIAI, L. Anotação de Corpus: Caracterização de Entidades Nomeadas em Tweets do Mercado Financeiro. Mestrado em Linguística—São Paulo: Programa de Pós-Graduação em Linguística da Universidade Federal de São Carlos, 2025.

PIMENTEL, C. L. A elaboração de um corpus oral: a etapa de transcrição da interação na sala de aula de português como lı́ngua adicional. mathesis—[s.l.] Pontifı́cia Universidade Católica do Rio Grande do Sul, 2016.

PING, W. et al. Deep voice 3: 2000-speaker neural text-to-speech. arXiv preprint arXiv:1710.07654, 2017.

PINHEIRO, V. et al. InferenceNet.Br: Expression of Inferentialist Semantic Content of the Portuguese Language. (T. A. S. Pardo et al., Eds.)Computational Processing of the Portuguese Language. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2010.

PIRES, I.; CASELI, H.; NERIS, V. Design de um chatbot para o diálogo com universitários com possível perfil depressivo. Anais Estendidos do XXIII Simpósio Brasileiro de Computação Aplicada à Saúde. Anais...Porto Alegre, RS, Brasil: SBC, a2023. Disponível em: <https://sol.sbc.org.br/index.php/sbcas_estendido/article/view/25323>

PIRES, R. et al. Sabiá: Portuguese Large Language Models. (M. C. Naldi, R. A. C. Bianchi, Eds.)Intelligent Systems. Anais...Cham: Springer Nature Switzerland, b2023.

PLACANI, A. Anthropomorphism in AI: hype and fallacy. AI and Ethics, p. 1–8, 2024.

PLANK, B.; HOVY, D.; SØGAARD, A. Linguistically debatable or just plain wrong? (K. Toutanova, H. Wu, Eds.)Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Anais...Baltimore, Maryland: Association for Computational Linguistics, jun. 2014. Disponível em: <https://aclanthology.org/P14-2083>

POESIO, M.; STUCKARDT, R.; VERSLEY, Y. Anaphora Resolution: Algorithms, Resources, and Applications. 1. ed. [s.l.] Springer, 2016.

PONTIKI, M. et al. SemEval-2014 Task 4: Aspect Based Sentiment Analysis. Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014). Anais...Association for Computational Linguistics, 2014. Disponível em: <https://aclanthology.org/S14-2004/>

POPIEL, S. J.; MCRAE, K. The figurative and literal senses of idioms, or all idioms are not used equally. Journal of Psycholinguistic Research, v. 17, n. 6, p. 475–487, 1 nov. 1988.

POPOVIĆ, M. chrF++: words helping character n-grams. Proceedings of the second conference on machine translation. Anais...2017.

PORTER, M. F. An algorithm for suffix stripping. Program, v. 14, n. 3, p. 130–137, 1980.

PORTET, F. et al. Automatic generation of textual summaries from neonatal intensive care data. Artificial Intelligence, v. 173, n. 7–8, p. 789–816, 2009.

POSNER, J.; RUSSELL, J. A.; PETERSON, B. S. The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology. Development and psychopathology, v. 17, n. 3, p. 715–734, 2005.

PRABHAKARAN, V.; RAMBOW, O. Written Dialog and Social Power: Manifestations of Different Types of Power in Dialog Behavior. Proceedings of the Sixth International Joint Conference on Natural Language Processing. Anais...Nagoya, Japan: Asian Federation of Natural Language Processing, out. 2013. Disponível em: <https://aclanthology.org/I13-1025>

PRADHAN, S. et al. CoNLL-2011 shared task: Modeling unrestricted coreference in ontonotes. Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task. Anais...Portland, Oregon: Association for Computational Linguistics, 2011.

PRADHAN, S. et al. CoNLL-2012 shared task: Modeling multilingual unrestricted coreference in OntoNotes. Proceedings of Joint Conference on Empirical Methods in Natural Language Processing and Conference on Natural Language Learning - Shared Task. Anais...Jeju Island, Korea: 2012.

PRADHAN, S. et al. Scoring Coreference Partitions of Predicted Mentions: A Reference Implementation. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. Anais...Baltimore, MD, USA: 2014. Disponível em: <http://aclweb.org/anthology/P/P14/P14-2006.pdf>

PRATAP, V. et al. Massively Multilingual ASR: 50 Languages, 1 Model, 1 Billion Parameters., a2020. Disponível em: <https://arxiv.org/abs/2007.03001>

PRATAP, V. et al. MLS: A Large-Scale Multilingual Dataset for Speech Research. Proc. Interspeech 2020, p. 2757–2761, b2020.

PRZEPIÓRKOWSKI, A. et al. Extended phraseological information in a valence dictionary for NLP applications. Proceedings of Workshop on Lexical and Grammatical Resources for Language Processing. Anais...Dublin, Ireland: Association for Computational Linguistics; Dublin City University, ago. 2014. Disponível em: <https://aclanthology.org/W14-5811>

PURINGTON, A. et al. " Alexa is my new BFF" Social Roles, User Satisfaction, and Personification of the Amazon Echo. Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems. Anais...2017.

PURVER, M. et al. Split Utterances in Dialogue: a Corpus Study. Proceedings of the SIGDIAL 2009 Conference. Anais...London, UK: Association for Computational Linguistics, set. 2009. Disponível em: <https://aclanthology.org/W09-3937>

PURVER, M. R. J. The theory and use of clarification requests in dialogue. tese de doutorado—[s.l.] University of London, 2004.

QUARESMA, P.; RODRIGUES, I. Using dialogues to access semantic knowledge in a web IR system. Computational Processing of the Portuguese Language: 6th International Workshop, PROPOR 2003 Faro, Portugal, June 26–27, 2003 Proceedings 6. Anais...Springer, 2003. Disponível em: <https://doi.org/10.1007/3-540-45011-4_32>

QUARESMA, P.; RODRIGUES, I. A Question-Answering System for Portuguese Juridical Documents. Proceedings of the 10th International Conference on Artificial Intelligence and Law. Anais...: ICAIL ’05.New York, NY, USA: Association for Computing Machinery, 2005. Disponível em: <https://doi.org/10.1145/1165485.1165536>

QUINTANILHA, I. M.; NETTO, S. L.; BISCAINHO, L. W. P. An open-source end-to-end ASR system for Brazilian Portuguese using DNNs built from newly assembled corpora. Journal of Communication and Information Systems, v. 35, n. 1, p. 230–242, 2020.

QUINTANO, L.; RODRIGUES, I. Managing dialog and access control in natural language querying. Computational Processing of the Portuguese Language: 6th International Workshop, PROPOR 2003 Faro, Portugal, June 26–27, 2003 Proceedings 6. Anais...Springer, 2003. Disponível em: <https://doi.org/10.1007/3-540-45011-4_33>

RABINER, L. R.; JUANG, B. H. Fundamentals of Speech Recognition. [s.l.] Pearson Education, 1993.

RADEMAKER, A. et al. Universal Dependencies for Portuguese. Proceedings of the Fourth International Conference on Dependency Linguistics (Depling 2017). Anais...Pisa,Italy: Linköping University Electronic Press, set. 2017. Disponível em: <https://aclanthology.org/W17-6523>

RADEV, D. R. A common theory of information fusion from multiple text sources step one: cross-document structure. 1st SIGdial workshop on Discourse and Dialogue. Anais...2000.

RADFORD, A. et al. Robust speech recognition via large-scale weak supervision. arXiv preprint arXiv:2212.04356, 2022.

RAFFEL, C. et al. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. Journal of Machine Learning Research, v. 21, n. 140, p. 1–67, 2020.

RAHMAN, A.; NG, V. Coreference Resolution with World Knowledge. Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies. Anais...Portland, Oregon, USA: b2011. Disponível em: <http://www.aclweb.org/anthology/P11-1082>

RAHMAN, A.; NG, V. Narrowing the modeling gap: a cluster-ranking approach to coreference resolution. Journal of Artificial Intelligence Research, p. 469–521, a2011.

RAJI, D. et al. AI and the Everything in the Whole Wide World Benchmark. (J. Vanschoren, S. Yeung, Eds.)Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks. Anais...Curran, 2021. Disponível em: <https://datasets-benchmarks-proceedings.neurips.cc/paper_files/paper/2021/file/084b6fbb10729ed4da8c3d3f5a3ae7c9-Paper-round2.pdf>

RAJPURKAR, P. et al. SQuAD: 100,000+ Questions for Machine Comprehension of Text. (J. Su, K. Duh, X. Carreras, Eds.)Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. Anais...Austin, Texas: Association for Computational Linguistics, nov. 2016. Disponível em: <https://aclanthology.org/D16-1264>

RAMISCH, C. Multiword Expressions Acquisition: A Generic and Open Framework. [s.l.] Springer, 2015. v. XIVp. 230

RAMISCH, C. et al. DeQue: A Lexicon of Complex Prepositions and Conjunctions in French. Proceedings of LREC 2016. Anais...Portoroz, Slovenia: ELRA, a2016.

RAMISCH, C. et al. How Naked is the Naked Truth? A Multilingual Lexicon of Nominal Compound Compositionality. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Anais...Berlin, Germany: ACL, b2016.

RAMISCH, C. et al. Edition 1.1 of the PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions. Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018). Anais...Santa Fe, NM, USA: ACL, a2018.

RAMISCH, C. et al. A Corpus Study of Verbal Multiword Expressions in Brazilian Portuguese. Computational Processing of the Portuguese Language 13th International Conference, PROPOR 2018, Canela, Brazil, September 24–26, 2018, Proceedings. Anais...: Lecture Notes em Artificial Intelligence.Cham, Switzerland: Springer International Publishing, b2018.

RAMISCH, C. et al. Edition 1.2 of the PARSEME Shared Task on Semi-supervised Identification of Verbal Multiword Expressions. Proceedings of the Joint Workshop on Multiword Expressions and Electronic Lexicons. Anais...online: Association for Computational Linguistics, 2020. Disponível em: <https://www.aclweb.org/anthology/2020.mwe-1.14>

RAMISCH, C. Multiword expressions in computational linguistics: down the rabbit hole and through the looking glass. tese de doutorado—Marseille, France: Aix Marseille University, 2023.

RAMISCH, C.; BESACIER, L.; KOBZAR, A. How hard is it to automatically translate phrasal verbs from English to French? MT Summit 2013 Workshop on Multi-word Units in Machine Translation and Translation Technology. Anais...Nice, France: 2013.

RAMISCH, C.; VILLAVICENCIO, A. Computational Treatment of Multiword Expressions. Em: MITKOV, R. (Ed.). The Oxford Handbook of Computational Linguistics. 2nd. ed. [s.l.] Oxford University Press, 2018.

RANCHHOD, E.; MOTA, C.; BAPTISTA, J. A Computational Lexicon of Portuguese for Automatic Text Parsing. SIGLEX99: Standardizing Lexical Resources. Anais...1999. Disponível em: <https://aclanthology.org/W99-0511>

RAO, K. S.; KOOLAGUDI, S. G.; VEMPADA, R. R. Emotion recognition from speech using global and local prosodic features. International journal of speech technology, v. 16, p. 143–160, 2013.

RASO, T. et al. O projeto C-ORAL-BRASIL. CHIMERA: Revista de Corpus de Lenguas Romances y Estudios Lingüı́sticos, v. 1, p. 31–67, 2015.

RASO, T.; MELLO, H. C-ORAL–BRASIL I: corpus de referência do português brasileiro falado informal. Belo Horizonte: Editora UFMG, 2012a.

RASO, T.; MELLO, H. C-ORAL–BRASIL I: corpus de referência do português brasileiro falado informal. A general presentation. Speech and Corpora, p. 16, b2012.

RASO, T.; TEIXEIRA, B.; BARBOSA, P. Modelling automatic detection of prosodic boundaries for Brazilian Portuguese spontaneous speech. Journal of Speech Sciences, v. 9, p. 105–128, set. 2020.

READ, J. et al. Sentence Boundary Detection: A Long Solved Problem? Proceedings of COLING 2012: Posters. Anais...Mumbai, India: The COLING 2012 Organizing Committee, dez. 2012. Disponível em: <https://aclanthology.org/C12-2096>

REAL, L.; FONSECA, E.; GONÇALO OLIVEIRA, H. Organizing the ASSIN 2 Shared Task. Proceedings of the ASSIN 2 Shared Task: Evaluating Semantic Textual Similarity and Textual Entailment in Portuguese: co-located with XII Symposium in Information and Human Language Technology (STIL 2019). Anais...2019. Disponível em: <https://ceur-ws.org/Vol-2583/1_ASSIN-2.pdf>

REAL, L.; FONSECA, E.; GONÇALO OLIVEIRA, H. The ASSIN 2 Shared Task: A Quick Overview. Computational Processing of the Portuguese Language: 14th International Conference, PROPOR 2020, Evora, Portugal, March 2–4, 2020, Proceedings. Anais...Berlin, Heidelberg: Springer-Verlag, 2020. Disponível em: <https://doi.org/10.1007/978-3-030-41505-1_39>

RECASENS, M.; HOVY, E. H. BLANC: Implementing the Rand index for coreference evaluation. Natural Language Engineering, v. 17, n. 4, p. 485–510, 2011.

REDDY, S.; MCCARTHY, D.; MANANDHAR, S. An Empirical Study on Compositionality in Compound Nouns. Proceedings of 5th International Joint Conference on Natural Language Processing. Anais...Chiang Mai, Thailand: Asian Federation of Natural Language Processing, nov. 2011. Disponível em: <https://aclanthology.org/I11-1024>

REI, R. et al. COMET: A Neural Framework for MT Evaluation. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Anais...Online: Association for Computational Linguistics, nov. 2020. Disponível em: <https://aclanthology.org/2020.emnlp-main.213>

REIS, E. S.; SILVA, L. A. DA. Planejamento e replanejamento dos turnos conversacionais. Cadernos do CNLF, v. 17, n. 2, p. 1–2013, 2013.

REITER, E. et al. Choosing Words in Computer-generated Weather Forecasts. Artificial Intelligence, v. 167, n. 1-2, p. 137–169, set. 2005.

REITER, E. An Architecture for Data-to-text Systems. Proceedings of ENLG-2007. Anais...: ENLG’07.Germany: Association for Computational Linguistics, 2007. Disponível em: <http://dl.acm.org/citation.cfm?id=1610163.1610180>

REITER, E. A Structured Review of the Validity of BLEU. Computational Linguistics, v. 44, n. 3, p. 393–401, 2018.

REITER, E.; DALE, R. Building natural language generation systems. New York, NY, USA: Cambridge University Press, 2000.

REITER, E.; ROBERTSON, R.; OSMAN, L. M. Lessons from a failure: Generating tailored smoking cessation letters. Artificial Intelligence, v. 144, n. 1, p. 41–58, 2003.

RESNIK, P.; LIN, J. Evaluation of NLP systems. Em: The handbook of computational linguistics and natural language processing. [s.l.] Wiley Online Library, 2010. p. 271–295.

REVIEW, M. T. Um aplicativo de Inteligência Artificial que “desnudava” mulheres mostra como as deepfakes prejudicam os mais vulneráveis. Disponível em: < https://mittechreview.com.br/um-aplicativo-de-inteligencia-artificial-que-desnudava-mulheres-mostra-como-as-deepfakes-prejudicam-os-mais-vulneraveis/>. Acesso em: 28 ago. 2023.

RIBEIRO, M. T. et al. Beyond Accuracy: Behavioral Testing of NLP Models with CheckList. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Anais...Online: Association for Computational Linguistics, jul. 2020. Disponível em: <https://aclanthology.org/2020.acl-main.442>

RIESER, V.; LEMON, O. Reinforcement learning for adaptive dialogue systems: a data-driven methodology for dialogue management and natural language generation. [s.l.] Springer Science & Business Media, 2011.

RIZZOLATTI, G.; ARBIB, M. A. Language within our grasp. Trends in Neurosciences, v. 21, n. 5, p. 188–194, 1998.

ROBERTS, A. et al. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. [s.l.] Google, 2019.

ROBERTS, F.; FRANCIS, A. L.; MORGAN, M. The interaction of inter-turn silence with prosodic cues in listener perceptions of “trouble” in conversation. Speech communication, v. 48, n. 9, p. 1079–1093, 2006.

ROCHA, E. B.; PIMENTEL, M.; DINIZ, M. C. Desenvolvimento de um Modelo da Participação em Bate papo seguindo a abordagem Design Science Research. Anais do X Simpósio Brasileiro de Sistemas de Informação. Anais...Porto Alegre, RS, Brasil: SBC, 2014. Disponível em: <https://sol.sbc.org.br/index.php/sbsi/article/view/6099>

ROCHA, M. A corpus-based study of anaphora in English and Portuguese, Corpus-based and Computational Approaches to Discourse Anaphora. Em: [s.l.] John Benjamins Publishing Company, 2000. p. 81–94.

ROCHA, P.; SANTOS, D. CLEF: Abrindo a porta à participação internacional em avaliação de RI do português. Em: SANTOS, D. (Ed.). Avaliação conjunta: um novo paradigma no processamento computacional da língua portuguesa. Lisboa, Portugal: IST Press, 2007. p. 143–158.

RODRIGUES, I. M. G. Fala e movimentos do corpo na interacção face a face: estratégias de reparação e de (des) focalização e co-funções conversacionais na manutenção de vez. tese de doutorado—[s.l.] Universidade do Porto, 2003.

RODRIGUES, R.; GOMES, P. RAPPORT — A Portuguese Question-Answering System. (F. Pereira et al., Eds.)Progress in Artificial Intelligence. Anais...Cham: Springer International Publishing, 2015.

ROGERS, A. Changing the World by Changing the Data. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Anais...Online: Association for Computational Linguistics, ago. 2021. Disponível em: <https://aclanthology.org/2021.acl-long.170>

ROHANIAN, O. et al. Verbal Multiword Expressions for Identification of Metaphor. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Anais...Online: Association for Computational Linguistics, jul. 2020. Disponível em: <https://aclanthology.org/2020.acl-main.259>

ROLLER, S.; SCHULTE IM WALDE, S. Feature Norms of German Noun Compounds. (V. Kordoni et al., Eds.)Proceedings of the 10th Workshop on Multiword Expressions (MWE). Anais...Gothenburg, Sweden: Association for Computational Linguistics, abr. 2014. Disponível em: <https://aclanthology.org/W14-0818>

ROLLER, S.; SCHULTE IM WALDE, S.; SCHEIBLE, S. The (Un)expected Effects of Applying Standard Cleansing Models to Human Ratings on Compositionality. Proceedings of the 9th Workshop on Multiword Expressions. Anais...Atlanta, Georgia, USA: Association for Computational Linguistics, jun. 2013. Disponível em: <https://aclanthology.org/W13-1005>

RONCARATI, C. As cadeias do texto: construindo sentidos. [s.l.] Parábola, 2010.

ROSÉN, V. et al. MWEs in Treebanks: From Survey to Guidelines. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16). Anais...Portorož, Slovenia: European Language Resources Association (ELRA), 2016. Disponível em: <https://aclanthology.org/L16-1368>

ROSSANO, F. Gaze in conversation. The handbook of conversation analysis, p. 308–329, 2012.

ROSSI, D. et al. Identifying pedagogical intervention in MOOCs learning processes: a conversational agent proposal. Anais do XXXII Simpósio Brasileiro de Informática na Educação. Anais...Porto Alegre, RS, Brasil: SBC, 2021. Disponível em: <https://sol.sbc.org.br/index.php/sbie/article/view/18112>

ROTHE, S.; NARAYAN, S.; SEVERYN, A. Leveraging Pre-trained Checkpoints for Sequence Generation Tasks. Transactions of the Association for Computational Linguistics, v. 8, p. 264–280, 2020.

RUANE, E.; BIRHANE, A.; VENTRESQUE, A. Conversational AI: Social and Ethical Considerations. AICS. Anais...2019. Disponível em: <https://ceur-ws.org/Vol-2563/aics_12.pdf>

RUITER, J. P. DE. Turn-Taking. Em: The Oxford Handbook of Experimental Semantics and Pragmatics. [s.l.] Oxford University Press, 2019.

RUPPENHOFER, J. et al. FrameNet II: Extended theory and practice. [s.l: s.n.].

RUSSEL, S. Human Compatible Artificial Intelligence and the Problem of Control. [s.l.] Penguin Books, 2019.

RUSSELL, S.; NORVIG, P. Artificial Intelligence: A Modern Approach. 3rd. ed. USA: Prentice Hall Press, 2009.

SACKS, H.; SCHEGLOFF, E. A.; JEFFERSON, G. A simplest systematics for the organization of turn taking for conversation. Em: Studies in the organization of conversational interaction. [s.l.] Elsevier, 1978. p. 7–55.

SADOCK, J. Speech acts. Em: The handbook of pragmatics. [s.l.] Wiley Online Library, 2006. p. 53–73.

SAEKI, T. et al. Virtuoso: Massive Multilingual Speech-Text Joint Semi-Supervised Learning for Text-To-Speech., 2023. Disponível em: <https://arxiv.org/abs/2210.15447>

SAG, I. A. et al. Multiword Expressions: A Pain in the Neck for NLP. Conference on Intelligent Text Processing and Computational Linguistics. Anais...2002. Disponível em: <https://api.semanticscholar.org/CorpusID:1826481>

SALESKY, E. et al. The multilingual tedx corpus for speech recognition and translation. arXiv preprint arXiv:2102.01757, 2021.

SALOMÃO, M. M. M. FrameNet Brasil: A work in progress. Calidoscópio, v. 7, p. 171–182, 2009.

SALTON, G.; ALLAN, J. Text retrieval using the vector processing model. dez. 1994.

SANCHES, M. F. et al. Textual Datasets For Portuguese-Brazilian Language Models. Anais do IV Dataset Showcase Workshop. Anais...SBC, 2022. Disponível em: <https://doi.org/10.5753/dsw.2022.224294>

SANG, E. F. T. K. Introduction to the CoNLL-2002 Shared Task: Language-Independent Named Entity Recognition. Proceedings of CoNLL-2002. Anais...Taipei, Taiwan: 2002. Disponível em: <https://aclanthology.org/W02-2024/>

SANTANA, B. P. Morfologia ornamental: as vogais temáticas do português brasileiro o Unitex-PB. mathesis—Curitiba, PR: Universidade Federal do Paraná, Setor de Ciências Humanas, Programa de Pós-Graduação em Letras, 2019.

SANTHANAM, S.; SHAIKH, S. A survey of natural language generation techniques with a focus on dialogue systems-past, present and future directions. arXiv preprint arXiv:1906.00500, 2019.

SANTOS, D. O projecto Processamento Computacional do Português: Balanço e perspectivas. (M. das Graças Volpe Nunes, Ed.)V Encontro para o processamento computacional da língua portuguesa escrita e falada (PROPOR 2000). Anais...São Paulo: ICMC/USP, 2000. Disponível em: <https://www.linguateca.pt/Diana/download/SantosPROPOR2000.pdf>

SANTOS, D. Evaluation in natural language processing., a2007. Disponível em: <http://www.linguateca.pt/Diana/download/EvaluationESSLLI07.pdf>

SANTOS, D. Avaliação conjunta. Em: SANTOS, D. (Ed.). Avaliação conjunta: um novo paradigma no processamento computacional da língua portuguesa. Lisboa, Portugal: IST Press, 2007c. p. 1–12.

SANTOS, D. (ED.). Avaliação conjunta: um novo paradigma no processamento computacional da língua portuguesa. Lisboa, Portugal: IST Press, 2007b.

SANTOS, D. Caminhos percorridos no mapa da portuguesificação: A Linguateca em perspectiva. Linguamática, v. 1, n. 1, p. 25–59, 2009.

SANTOS, D. et al. GikiP at GeoCLEF 2008: Joining GIR and QA forces for querying Wikipedia. Em: PETERS, C. et al. (Eds.). Evaluating Systems for Multilingual and Multimodal Information Access 9th Workshop of the Cross-Language Evaluation Forum, CLEF 2008, Aarhus, Denmark, September 17-19, 2008, Revised Selected Papers. [s.l.] Springer, 2009. p. 894–905.

SANTOS, D. et al. GikiCLEF: Crosscultural issues in multilingual information access. (N. Calzolari et al., Eds.)Proceedings of the International Conference on Language Resources and Evaluation (LREC 2010). Anais...Valletta, Malta: European Language Resources Association, 2010. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2010/pdf/272_Paper.pdf>

SANTOS, D. et al. (EDS.). Edição especial Págico - português mágico. [s.l.] Linguamática, 2012. v. 4

SANTOS, D. Evaluation contests in Portuguese: Linguateca’s contribution., 2021. Disponível em: <https://www.linguateca.pt/Diana/download/AvalConjLRE16May2021.pdf>

SANTOS, D. et al. DIP - Desafio de Identificação de Personagens: objectivo, organização, recursos e resultados. Linguamática, v. 15, n. 1, p. 3–30, 2023.

SANTOS, D.; CABRAL, L. M. GikiCLEF : Expectations and lessons learned. Em: PETERS, C. et al. (Eds.). Multilingual Information Access Evaluation, VOL I. [s.l.] Springer, 2010. p. 212–222.

SANTOS, D.; COSTA, L.; ROCHA, P. Cooperatively evaluating Portuguese morphology. (J. Baptista et al., Eds.)Computational Processing of the Portuguese Language: 6th International Workshop, PROPOR 2003. Faro, Portugal, June 2003 (PROPOR 2003). Anais...Berlin/Heidelberg: Springer Verlag, 2003.

SANTOS, D.; ROCHA, P. AvalON: uma iniciativa de avaliação conjunta para o português. (A. Mendes, T. Freitas, Eds.)Actas do XVIII Encontro Nacional da Associação Portuguesa de Linguística (APL 2002). Anais...Lisboa: APL, 2003. Disponível em: <https://www.linguateca.pt/Diana/download/SantosRochaAPL2002.pdf>

SANTOS, F. R. DOS et al. EDUARDO - A Semantic Model for Automatic Content Integration with an Conversational Intelligent Agent. Anais do XXII Simpósio Brasileiro de Sistemas Multimídia e Web. Anais...Porto Alegre, RS, Brasil: SBC, 2016. Disponível em: <https://sol.sbc.org.br/index.php/webmedia/article/view/5372>

SANTOS, F.; FREITAS, T. CORP-ORAL: Spontaneous Speech Corpus for European Portuguese. Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08). Anais...Marrakech, Morocco: European Language Resources Association (ELRA), 2008. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2008/pdf/331_paper.pdf>

SANTOS, J.; ALVES, A.; GONÇALO OLIVEIRA, H. Leveraging on Semantic Textual Similarity for developing a Portuguese dialogue system. International Conference on Computational Processing of the Portuguese Language. Anais...Springer, 2020. Disponível em: <https://doi.org/10.1007/978-3-030-41505-1_13>

SANTOS SILVA, D. DOS; PARABONI, I. Generating Spatial Referring Expressions in Interactive 3D Worlds. Spatial Cognition & Computation, v. 15, n. 03, p. 186–225, 2015.

SANTOS, V. G. et al. CORAA NURC-SP Minimal Corpus: a manually annotated corpus of Brazilian Portuguese spontaneous speech. Proc. IberSPEECH 2022. Anais...2022.

SARMENTO, C. DA S. Da Abordagem do Léxico em Livros Didáticos de Língua Portuguesa: os Anos Finais do Ensino Fundamental. mathesis—Brasília: UnB, 2019.

SARMENTO, L.; PINTO, A. S.; CABRAL, L. REPENTINO – a wide-scope gazetteer for entity recognition in portuguese. Proceedings of International Workshop on Computational Processing of the Portuguese Language. Anais...Springer, 2006.

SARTORI, L.; THEODOROU, A. A Sociotechnical Perspective for the Future of AI: Narratives, Inequalities, and Human Control. Ethics and Inf. Technol., v. 24, n. 1, mar. 2022.

SAURÍ, R. et al. TimeML Annotation Guidelines, Version 1.2.1., 2006. Disponível em: <https://nilsreiter.de/assets/2017-10-01-howto-annotation/timeml-1.2.1.pdf>

SAVARY, A. et al. Literal Occurrences of Multiword Expressions: Rare Birds That Cause a Stir. The Prague Bulletin of Mathematical Linguistics, v. 112, p. 5–54, 2019b2019b.

SAVARY, A. et al. PARSEME – parsing and multiword Expressions within a European multilingual network. Proc. of LTC 2015. Anais...Poznań: 2015.

SAVARY, A. et al. The PARSEME Shared Task on Automatic Identification of Verbal Multiword Expressions. Proceedings of the 13th Workshop on MWEs. Anais...Valencia, Spain: ACL, 2017.

SAVARY, A. et al. PARSEME multilingual corpus of verbal multiword expressions. Em: MARKANTONATOU, S. et al. (Eds.). Multiword expressions at length and in depth: Extended papers from the MWE 2017 workshop. Phraseology e Multiword Expressions. Berlin, Germany: Language Science Press, 2018. v. 2.

SAVARY, A. et al. Object-oriented lexical encoding of multiword expressions: Short and sweet. Lexique, n. 27, p. 87–120, 2020.

SAVARY, A. et al. PARSEME Meets Universal Dependencies: Getting on the Same Page in Representing Multiword Expressions. Northern European Journal of Language Technology, v. 9, p. 14, a2023.

SAVARY, A. et al. PARSEME corpus release 1.3. Proceedings of the 19th Workshop on Multiword Expressions (MWE 2023). Anais...Dubrovnik, Croatia: Association for Computational Linguistics, b2023.

SAVARY, A.; CORDEIRO, S.; RAMISCH, C. Without lexicons, multiword expression identification will never fly: A position statement. Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019). Anais...Florence, Italy: Association for Computational Linguistics, 2019a2019a. Disponível em: <https://aclanthology.org/W19-5110>

SCARTON, C. E.; ALUISIO, S. M. Towards a cross-linguistic VerbNet-style lexicon for Brazilian portuguese. Workshop on Creating Cross-language Resources for Disconnected Languages and Styles - CREDISLAS. Anais...ELRA, 2012.

SCHEGLOFF, E. A. Overlapping talk and the organization of turn-taking for conversation. Language in society, v. 29, n. 1, p. 1–63, 2000.

SCHEGLOFF, E. A.; JEFFERSON, G.; SACKS, H. The preference for self-correction in the organization of repair in conversation. Language, v. 53, n. 2, p. 361–382, 1977.

SCHEGLOFF, E. A.; SACKS, H. Opening up closings. Semiotica, 1973.

SCHLANGEN, D. Language tasks and language games: On methodology in current natural language processing research. arXiv preprint arXiv:1908.10747, 2019.

SCHLANGEN, D. Targeting the Benchmark: On Methodology in Current Natural Language Processing Research. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). Anais...Online: Association for Computational Linguistics, ago. 2021. Disponível em: <https://aclanthology.org/2021.acl-short.85>

SCHLANGEN, D. Norm Participation Grounds Language. Proceedings of the 2022 CLASP Conference on (Dis)embodiment. Anais...Gothenburg, Sweden: Association for Computational Linguistics, set. 2022. Disponível em: <https://aclanthology.org/2022.clasp-1.7>

SCHLANGEN, D. What A Situated Language-Using Agent Must be Able to Do: A Top-Down Analysis., b2023. Disponível em: <https://arxiv.org/abs/2302.08590>

SCHLANGEN, D. Dialogue games for benchmarking language understanding: Motivation, taxonomy, strategy. arXiv preprint arXiv:2304.07007, a2023.

SCHLANGEN, D. On General Language Understanding. (H. Bouamor, J. Pino, K. Bali, Eds.)Findings of the Association for Computational Linguistics: EMNLP 2023. Anais...Singapore: Association for Computational Linguistics, dez. c2023. Disponível em: <https://aclanthology.org/2023.findings-emnlp.591>

SCHLANGEN, D.; SKANTZE, G. A general, abstract model of incremental dialogue processing. Dialogue & Discourse, v. 2, n. 1, p. 83–111, 2011.

SCHMID, H. Part-of-Speech Tagging with Neural Networks., 1994. Disponível em: <https://arxiv.org/abs/cmp-lg/9410018>

SCHNEIDER, N. et al. SemEval-2016 Task 10: Detecting Minimal Semantic Units and their Meanings (DiMSUM). Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016). Anais...San Diego, California: Association for Computational Linguistics, 2016. Disponível em: <https://aclanthology.org/S16-1084>

SCHNEIDER, N.; SMITH, N. A. A Corpus and Model Integrating Multiword Expressions and Supersenses. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Anais...Denver, Colorado: Association for Computational Linguistics, 2015. Disponível em: <https://www.aclweb.org/anthology/N15-1177>

SCHONE, P.; JURAFSKY, D. Is Knowledge-Free Induction of Multiword Unit Dictionary Headwords a Solved Problem? (L. Lee, D. Harman, Eds.)Proceedings of the 2001 Conference on Empirical Methods in Natural Language Processing. Anais...2001.

SCHRÖDER, U. The interplay of verbal, vocal, and visual cues in the co-construction of the experience of alterity in exchange students’ talk. Journal of Pragmatics, v. 81, p. 21–35, 2015.

SCHULTE IM WALDE, S. et al. GhoSt-NN: A Representative Gold Standard of German Noun-Noun Compounds. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16). Anais...Portorož, Slovenia: European Language Resources Association (ELRA), 2016. Disponível em: <https://aclanthology.org/L16-1362>

SCHUSTER, M.; NAKAJIMA, K. Japanese and Korean voice search. 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Anais...2012.

SCHUSTER, M.; PALIWAL, K. K. Bidirectional recurrent neural networks. IEEE transactions on Signal Processing, v. 45, n. 11, p. 2673–2681, 1997.

SEARA, I. Estudo Estatístico dos Fonemas do Português Brasileiro Falado na Capital de Santa Catarina para Elaboração de Frases Foneticamente Balanceadas. tese de doutorado—[s.l.] Dissertação de Mestrado, Universidade Federal de Santa Catarina …, 1994.

SECO, N. et al. A Complex Evaluation Architecture for HAREM. (R. Vieira et al., Eds.)Computational Processing of the Portuguese Language: 7th International Workshop, PROPOR 2006. Anais...Springer, 2006.

SELLAM, T.; DAS, D.; PARIKH, A. P. BLEURT: Learning Robust Metrics for Text Generation. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020. Anais...2020. Disponível em: <https://doi.org/10.18653/v1/2020.acl-main.704>

SELLARS, W. Inference and Meaning. Mind, v. 62, n. 247, p. 313–338, 1953.

SENNRICH, R.; HADDOW, B.; BIRCH, A. Neural Machine Translation of Rare Words with Subword Units. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Anais...Berlin, Germany: Association for Computational Linguistics, ago. 2016. Disponível em: <https://aclanthology.org/P16-1162>

SENO, E. R. M. RHeSumaRST: um sumarizador automático de estruturas RST. mathesis—[s.l.] Universidade Federal de São Carlos, 2005.

SERBAN, I. et al. Building end-to-end dialogue systems using generative hierarchical neural network models. Proceedings of the AAAI conference on artificial intelligence. Anais...2016. Disponível em: <https://doi.org/10.48550/arXiv.1507.04808>

SERBAN, I. V. et al. A Survey of Available Corpora For Building Data-Driven Dialogue Systems: The Journal Version. Dialogue & Discourse, v. 9, n. 1, p. 1–49, 2018.

SERETAN, V. Syntax-Based Collocation Extraction. 1st. ed. Dordrecht, Netherlands: springer, 2011. v. 44

SERRA, C. R. Realização e percepção de fronteiras prosódicas no português do Brasil: fala espontânea e leitura. tese de doutorado—Rio de Janeiro: Universidade Federal do Rio de Janeiro, 2009.

SETTLES, B. Active Learning Literature Survey., 2010. Disponível em: <https://burrsettles.com/pub/settles.activelearning.pdf>

SHAPIRO, S. C. SNePS: A Logic for Natural Language Understanding and Commonsense Reasoning. Em: Natural Language Processing and Knowledge Representation: Language for Knowledge and Knowledge for Language. Cambridge, MA, USA: MIT Press, 2000. p. 175–195.

SHEN, J. et al. Natural tts synthesis by conditioning wavenet on mel spectrogram predictions. 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Anais...IEEE, 2018.

SHIMORINA, A.; BELZ, A. The Human Evaluation Datasheet: A Template for Recording Details of Human Evaluation Experiments in NLP. Proceedings of the 2nd Workshop on Human Evaluation of NLP Systems (HumEval). Anais...Dublin, Ireland: Association for Computational Linguistics, 2022. Disponível em: <https://aclanthology.org/2022.humeval-1.6>

SHMUELI, B. et al. Beyond Fair Pay: Ethical Implications of NLP Crowdsourcing. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Anais...Online: Association for Computational Linguistics, jun. 2021. Disponível em: <https://aclanthology.org/2021.naacl-main.295>

SHRIBERG, E. Preliminaries to a theory of speech disfluencies. tese de doutorado—[s.l.] University of California at Berkele, 1994.

SHRIBERG, E. To “errrr” is human: ecology and acoustics of speech disfluencies. Journal of the International Phonetic Association, v. 31, n. 1, p. 153–169, 2001.

SHUMAILOV, I. et al. AI models collapse when trained on recursively generated data. Nature, v. 631, n. 8022, p. 755–759, 2024.

SI, S. et al. Sentence Similarity Computation in Question Answering Robot. Journal of Physics: Conference Series, v. 1237, n. 2, p. 022093, jun. 2019.

SIDDHI, D.; VERGHESE, J. M.; BHAVIK, D. Survey on various methods of text to speech synthesis. International Journal of Computer Applications, v. 165, n. 6, 2017.

SIDNELL, J. Turn-continuation by self and by other. Discourse Processes, v. 49, n. 3-4, p. 314–337, 2012.

SIDNER, C. A progress report on the discourse and reference components of PAL. [s.l.] Massachusetts Institute of Tech Cambridge Artificial Intelligence LAB, 1978.

SILVA, E. DA; LATERZA, J.; FALEIROS, T. New State-of-the-Art for Question Answering on Portuguese SQuAD v1.1. Anais do X Symposium on Knowledge Discovery, Mining and Learning. Anais...Porto Alegre, RS, Brasil: SBC, a2022. Disponível em: <https://sol.sbc.org.br/index.php/kdmile/article/view/24974>

SILVA, E.; PARDO, T.; ROMAN, N. Etiquetagem morfossintática multigênero para o português do Brasil segundo o modelo Üniversal Dependencies̈. Anais do XIV Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana. Anais...Porto Alegre, RS, Brasil: SBC, 2023. Disponível em: <https://sol.sbc.org.br/index.php/stil/article/view/25438>

SILVA, F. L. V. DA et al. ABSAPT 2022 at IberLEF: Overview of the Task on Aspect-Based Sentiment Analysis in Portuguese. Procesamiento del Lenguaje Natural, v. 69, p. 199–205, b2022.

SILVA, J. F. DA. Resolução de correferência em múltiplos documentos utilizando aprendizado não supervisionado. Dissertação de Mestrado, Universidade de São Paulo, 2011.

SIMMONS, R.; SLOCUM, J. Generating English Discourse from Semantic Networks. Commun. ACM, v. 15, n. 10, p. 891–905, out. 1972.

SIMÕES, A.; GUINOVART, X. G. Bootstrapping a Portuguese WordNet from Galician, Spanish and English Wordnets. IberSPEECH Conference. Anais...2014. Disponível em: <https://api.semanticscholar.org/CorpusID:10377782>

SINCLAIR, J. (ED.). Collins COBUILD Dictionary of Phrasal Verbs. London, UK: Collins COBUILD, 1989.

SINGH, P. et al. Open Mind Common Sense: Knowledge Acquisition from the General Public. (R. Meersman, Z. Tari, Eds.)On the Move to Meaningful Internet Systems 2002: CoopIS, DOA, and ODBASE. Anais...Berlin, Heidelberg: Springer Berlin Heidelberg, 2002.

SINGH, Y. B.; GOEL, S. A systematic literature review of speech emotion recognition approaches. Neurocomputing, 2022.

SKANTZE, G. Error Handling in Spoken Dialogue Systems: Managing Uncertainty, Grounding and Miscommunication. tese de doutorado—[s.l.] KTH, 2007.

SKANTZE, G. Turn-taking in conversational systems and human-robot interaction: a review. Computer Speech & Language, v. 67, p. 101178, 2021.

SKANTZE, G.; DOĞRUÖZ, A. S. The Open-domain Paradox for Chatbots: Common Ground as the Basis for Human-like Dialogue. Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue. Anais...Prague, Czechia: Association for Computational Linguistics, set. 2023. Disponível em: <https://aclanthology.org/2023.sigdial-1.57>

SMADJA, F. A. Retrieving Collocations from Text: Xtract. cl, v. 19, n. 1, p. 143–177, 1993.

SMILEY, C. et al. When to Plummet and When to Soar: Corpus Based Verb Selection for Natural Language Generation. Proceedings of the 9th International Natural Language Generation conference. Anais...: INLG’16.Edinburgh, UK: Association for Computational Linguistics, 2016. Disponível em: <http://anthology.aclweb.org/W16-6606>

SMITH, G.; RUSTAGI, I. Mitigating Bias in Artificial Intelligence: An Equity Fluent Leadership Playbook. [s.l.] Berkeley Haas Center for Equity, Gender; Leadership, 2020.

SØGAARD, A. et al. What’s in a p-value in NLP? Proceedings of the Eighteenth Conference on Computational Natural Language Learning. Anais...Ann Arbor, Michigan: Association for Computational Linguistics, jun. 2014. Disponível em: <https://aclanthology.org/W14-1601>

SOHN, K. et al. FixMatch: simplifying semi-supervised learning with consistency and confidence. Proceedings of the 34th International Conference on Neural Information Processing Systems. Anais...: NIPS ’20.Red Hook, NY, USA: Curran Associates Inc., 2020.

SOON, W. M.; NG, H. T.; LIM, C. Y. A Machine Learning Approach to Coreference Resolution of Noun Phrases. Computational Linguistics, v. 27, n. 4, p. 521–544, 2001.

SOUSA, A. G. DE et al. Using a Domain Ontology to Bridge the Gap between User Intention and Expression in Natural Language Queries. ICEIS (1). Anais...2020.

SOUSA, C. S. C.; ANDRADE, I. M.; ALMEIDA, T. G. DE. A Monopolização de uma conversa informal: Uma descrição dos movimentos de continua ção a partir da linguística sistêmico-funcional. EntreLetras, v. 13, n. 1, p. 158–183, 2022.

SOUZA, B. B. DE. A interpretação de lı́nguas de sinais como ação conjunta: uma análise da interação entre o intérprete de turno e o intérprete de apoio. Trabalho de conclusão de curso. Universidade Federal de São Carlos, 2021.

SOUZA, E. DE. Construção e avaliação de um treebank padrão ouro. Mestrado—[s.l.] PUC-Rio, 2023.

SOUZA, E. DE; FREITAS, C. Explorando variações no tagset e na anotação Universal Dependencies (UD) para Português: Possibilidades e resultados com base no treebank PetroGold. Anais do XIV Simpósio Brasileiro de Tecnologia da Informação e da Linguagem Humana. Anais...Association for Computational Linguistics, 2023.

SOUZA, F.; NOGUEIRA, R.; LOTUFO, R. BERTimbau: pretrained BERT models for Brazilian Portuguese. (R. Cerri, R. C. Prati, Eds.)Proceedings of the 2020 Brazilian Conference on Intelligent Systems. Anais...Springer International Publishing, 2020.

SOUZA, J. W. DA C. Descrição linguística da complementaridade para a sumarização automática multidocumento. mathesis—[s.l.] Universidade Federal de São Carlos, 2015.

SOUZA, J. W. DA C. Aprofundamento da caracterização linguístico-computacional da complementaridade em um corpus jornalístico multidocumento. tese de doutorado—[s.l.] (Doutorado em Linguística) - Programa de Pós-Graduação em Linguística, Universidade Federal de São Carlos, 2019.

SPARCK JONES, K. Towards Better NLP System Evaluation. Human Language Technology: Proceedings of a Workshop held at Plainsboro, New Jersey, March 8-11, 1994. Anais...1994. Disponível em: <https://aclanthology.org/H94-1018>

SPARCK JONES, K. Natural language processing: a historical review. Em: Current issues in computational linguistics: in honour of Don Walker. [s.l.] Springer, 2001. p. 3–16.

SPARCK JONES, K.; GALLIERS, J. R. Evaluating Natural Language Processing Systems: An Analysis and Review. Lecture Notes in Computer Science, 1995.

SPEER, R.; CHIN, J.; HAVASI, C. ConceptNet 5.5: An Open Multilingual Graph of General Knowledge. CoRR, v. abs/1612.03975, 2016.

SPINDOLA, S. et al. Interpretability of Attention Mechanisms in a Portuguese-Based Question Answering System about the Blue Amazon. Anais do XVIII Encontro Nacional de Inteligência Artificial e Computacional. Anais...Porto Alegre, RS, Brasil: SBC, 2021. Disponível em: <https://sol.sbc.org.br/index.php/eniac/article/view/18302>

SRIPADA, S.; GAO, F. Summarizing Dive Computer Data: A Case Study in Integrating Textual and Graphical Presentations of Numerical Data. Workshop on Multimodal Output Generation. Anais...: MOG’07.Association for Computational Linguistics, 2007.

SRIPADA, S.; REITER, E.; DAVY, I. SumTime-Mousam: Configurable marine weather forecast generator. Expert Update, v. 6, n. 3, p. 4–10, fev. 2004.

STAB, C. et al. Argumentation Mining in Persuasive Essays and Scientific Articles from the Discourse Structure Perspective. ArgNLP. Anais...2014.

STEIN, F. O dispositivo para o gerenciamento de sobreposições de vozes na conversa cotidiana em português brasileiro. Salão de Iniciação Cientı́fica (22.: 2010 out. 18-22: Porto Alegre, RS). Livro de resumos. Porto Alegre: UFRGS., 2010.

STEVENS, S. S. A Scale for the Measurement of the Psychological Magnitude Pitch. Acoustical Society of America Journal, v. 8, n. 3, p. 185, jan. 1937.

STIVERS, T. Sequence Organization. Em: The handbook of conversation analysis. [s.l.] Wiley Online Library, 2013. v. 191.

STYMNE, S.; CANCEDDA, N.; AHRENBERG, L. Generation of Compound Words in Statistical Machine Translation into Compounding Languages. Computational Linguistics, p. 1—–42, 2013.

SUCHANEK, F. M.; KASNECI, G.; WEIKUM, G. Yago: a core of semantic knowledge. Proceedings of the 16th international conference on World Wide Web. Anais...2007.

SUNDAR, A.; HECK, L. Multimodal Conversational AI: A Survey of Datasets and Approaches. Proceedings of the 4th Workshop on NLP for Conversational AI. Anais...Dublin, Ireland: Association for Computational Linguistics, 2022. Disponível em: <https://aclanthology.org/2022.nlp4convai-1.12>

SUNKARA, M. et al. Multimodal Semi-Supervised Learning Framework for Punctuation Prediction in Conversational Speech. Proc. Interspeech 2020. Anais...2020.

SUNKARA, M. et al. Neural Inverse Text Normalization. CoRR, v. abs/2102.06380, 2021.

SUTSKEVER, I.; VINYALS, O.; LE, Q. V. Sequence to Sequence Learning with Neural Networks. (Z. Ghahramani et al., Eds.)Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada. Anais...2014. Disponível em: <https://proceedings.neurips.cc/paper/2014/hash/a14ac55a4f27472c5d894ec1c3c743d2-Abstract.html>

TABOADA, M.; MANN, W. C. Rhetorical structure theory: Looking back and moving ahead. Discourse studies, v. 8, n. 3, p. 423–459, 2006.

TACHIBANA, H.; UENOYAMA, K.; AIHARA, S. Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention. arXiv preprint arXiv:1710.08969, 2017.

TAN, L.; PAL, S. Manawi: Using Multi-Word Expressions and Named Entities to Improve Machine Translation. Proceedings of the 14th Machine Translation Summint. Workshop on Multi-word units in Machine Translation and Translation Technologies. Anais...2014.

TAN, X. et al. A survey on neural speech synthesis. arXiv preprint arXiv:2106.15561, 2021.

TANAKA, E. et al. Cem Mil Podcasts: A Spoken Portuguese Document Corpus. arXiv preprint arXiv:2209.11871, 2022.

TASLIMIPOOR, S.; ROHANIAN, O.; HA, L. A. Cross-lingual Transfer Learning and Multitask Learning for Capturing Multiword Expressions. Proceedings of the Joint Workshop on Multiword Expressions and WordNet (MWE-WN 2019). Anais...Florence, Italy: Association for Computational Linguistics, ago. 2019. Disponível em: <https://aclanthology.org/W19-5119>

TAYYAR MADABUSHI, H. et al. AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Models. Findings of the Association for Computational Linguistics: EMNLP 2021. Anais...Punta Cana, Dominican Republic: Association for Computational Linguistics, nov. 2021. Disponível em: <https://aclanthology.org/2021.findings-emnlp.294>

TAYYAR MADABUSHI, H. et al. SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding. Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022). Anais...Seattle, United States: Association for Computational Linguistics, jul. 2022. Disponível em: <https://aclanthology.org/2022.semeval-1.13>

TEDESCHI, S. et al. What’s the Meaning of Superhuman Performance in Today’s NLU? Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Anais...Toronto, Canada: Association for Computational Linguistics, jul. 2023. Disponível em: <https://aclanthology.org/2023.acl-long.697>

TEIXEIRA, A. L. R. et al. DaMata: A robot-journalist covering the Brazilian Amazon deforestation. Proceedings of the 13th International Conference on Natural Language Generation. Anais...2020.

TEIXEIRA, B. H. F. Detecção automática de fronteiras prosódicas na fala espontânea. tese de doutorado—Belo Horizonte: Universidade Federal de Minas Gerais, 2022.

TEIXEIRA, B. H. F.; MITTMAN, M. M. Acoustic Models for the Automatic Identification of Prosodic Boundaries in Spontaneous Speech. Revista de Estudos da Linguagem, v. 26, n. 4, p. 1455–1488, 2018.

TEIXEIRA, B.; BARBOSA, P.; RASO, T. Automatic Detection of Prosodic Boundaries in Brazilian Portuguese Spontaneous Speech. (A. Villavicencio et al., Eds.)Computational Processing of the Portuguese Language. Anais...Cham: Springer International Publishing, 2018.

TEIXEIRA, J. P. et al. Phonetic Events from the Labeling the European Portuguese DataBase for Speech Synthesis, FEUP/IPBDB. Seventh European Conference on Speech Communication and Technology. Anais...2001.

TEIXEIRA, J. P.; FREITAS, D.; FUJISAKI, H. Prediction of Fujisaki model’s phrase commands. Eighth European Conference on Speech Communication and Technology. Anais...2003.

TENNANT, H. R. Evaluation of Natural Language Processors. tese de doutorado—[s.l.] University of Illinois Urbana-Champaign, 1980.

TESCH, L. M. O uso de digressões em textos orais. Filologia e Linguı́stica Portuguesa, v. 17, n. 2, p. 273–293, 2015.

TESNIÈRE, L. Eléments de Syntaxe Structurale. Paris: Klincksieck, 1959.

THAKKAR, M.; PISE, N. Survey of Available Datasets for Designing Task Oriented Dialogue Agents. 2019 International Conference on Mechatronics, Remote Sensing, Information Systems and Industrial Information Technologies (ICMRSISIIT). Anais...2019. Disponível em: <https://doi.org/10.1109/ICMRSISIIT46373.2020.9405898>

THEUNE, M. et al. From data to speech: a general approach. Natural Language Engineering, v. 7, n. 1, p. 47–86, 2001.

THOMAS, R. L.; UMINSKY, D. Reliance on metrics is a fundamental challenge for AI. Patterns, v. 3, n. 5, 2022.

TJOA, E.; GUAN, C. A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI. IEEE Transactions on Neural Networks and Learning Systems, v. 32, n. 11, p. 4793–4813, 2021.

TOKUDA, K. et al. Speech parameter generation algorithms for HMM-based speech synthesis. 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No. 00CH37100). Anais...IEEE, 2000.

TOMASELLO, M. The usage-based theory of language acquisition. Em: BAVIN, E. L.; NAIGLES, L. R. E. (Eds.). The Cambridge Handbook of Child Language. Cambridge Handbooks em Language e Linguistics. 2. ed. [s.l.] Cambridge University Press, 2015. p. 89–106.

TORRENT, T. T. et al. Copa 2014 FrameNet Brasil: a frame-based trilingual electronic dictionary for the Football World Cup. Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: System Demonstrations. Anais...Dublin, Ireland: Dublin City University; Association for Computational Linguistics, ago. 2014. Disponível em: <https://aclanthology.org/C14-2003>

TORRENT, T. T.; ELLSWORTH, M. Behind the Labels: Criteria for Defining Analytical Categories in FrameNet Brasil. Veredas-Revista de Estudos Linguisticos, v. 17, n. 1, p. 44–66, 2013.

TOSCANO, M. E. S. As relações interpessoais e a correção na lı́ngua falada. Cadernos de Linguagem e Sociedade, v. 5, p. 119–119, 2001.

TRANCOSO, I. et al. Corpus de diálogo CORAL. PROPOR’98, 1998.

TRUESWELL, J. C.; TANENHAUS, M. K. Approaches to studying world-situated language use: Bridging the language-as-product and language-as-action traditions. [s.l.] MIT Press, 2005.

TSVETKOV, Y.; WINTNER, S. Identification of Multi-word Expressions by Combining Multiple Linguistic Information Sources. Proceedings of the Conference on Empirical Methods in Natural Language Processing. Anais...: EMNLP ’11.Stroudsburg, PA, USA: Association for Computational Linguistics, 2011.

TSVETKOV, Y.; WINTNER, S. Extraction of multi-word expressions from small parallel corpora. Natural Language Engineering, v. 18, n. 04, p. 549–573, 2012.

TURNER, R. et al. Generating Spatio-temporal Descriptions in Pollen Forecasts. Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Demonstrations. Anais...: EACL’06.Trento, Italy: Association for Computational Linguistics, 2006. Disponível em: <http://dl.acm.org/citation.cfm?id=1608974.1608998>

ULMER, D. et al. Experimental Standards for Deep Learning in Natural Language Processing Research. Findings of the Association for Computational Linguistics: EMNLP 2022. Anais...Abu Dhabi, United Arab Emirates: Association for Computational Linguistics, dez. 2022. Disponível em: <https://aclanthology.org/2022.findings-emnlp.196>

UNESCO. Beijing consensus on artificial intelligence and education. UNESCO Paris, 2019.

UNESCO, D. G. Recomendação sobre a Ética da Inteligência Artificial. Disponível em: < https://unesdoc.unesco.org/ark:/48223/pf0000381137_por >. Acesso em: 28 ago. 2023.

UNICEF. Declaração Universal dos Direitos Humanos. Disponível em: < https://www.unicef.org/brazil/declaracao-universal-dos-direitos-humanos>. Acesso em: 28 ago. 2023.

UZÊDA, V. R.; PARDO, T. A. S.; NUNES, M. G. V. A comprehensive comparative evaluation of RST-based summarization methods. ACM Transactions on Speech and Language Processing (TSLP), v. 6, n. 4, p. 1–20, 2010.

VALLE, R. et al. Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis. arXiv preprint arXiv:2005.05957, 2020.

VAN DEEMTER, K. et al. Toward a computational psycholinguistics of reference production. Topics in cognitive science, v. 4, n. 2, p. 166–183, 2012.

VAPNIK, V. N. Statistical Learning Theory. [s.l.] Wiley, 1998.

VAPNIK, V. N. The Nature of Statistical Learning Theory. 2. ed. New York, NY: Springer, 2000. p. 314

VARGAS, F. A.; PARDO, T. A. S. Aspect clustering methods for sentiment analysis. Proceedings of International conference on computational processing of the Portuguese language. Anais...Springer, 2018.

VASWANI, A. et al. Attention is All you Need. (I. Guyon et al., Eds.)Advances in Neural Information Processing Systems. Anais...Curran Associates, Inc., 2017. Disponível em: <https://proceedings.neurips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html>

VEAUX, C. et al. CSTR VCTK corpus: English multi-speaker corpus for CSTR voice cloning toolkit. University of Edinburgh. The Centre for Speech Technology Research (CSTR), 2017.

VERHAGEN, M. et al. SemEval-2010 Task 13: TempEval-2. Proceedings of the 5th International Workshop on Semantic Evaluation, SemEval. Anais...2010. Disponível em: <https://www.aclweb.org/anthology/S10-1010.pdf>

VIEIRA, F. E.; FARACO, C. A. Texto e discurso. Escrever na universidade. [s.l.] Parábola, 2019.

VIEIRA, R. et al. Coreference and anaphoric relations of demonstrative noun phrases in multilingual corpus. Anaphora Processing: linguistic, cognitive and computational modeling, p. 385–403, 2005.

VIEIRA, R.; GONÇALVES, P. N.; SOUZA, J. G. C. DE. Processamento computacional de anáfora e correferência. Revista de Estudos da Linguagem, v. 16, n. 1, 2012.

VIETHEN, J.; DALE, R. GRE3D7: A Corpus of Distinguishing Descriptions for Objects in Visual Scenes. UCNLG+Eval: Language Generation and Evaluation Workshop. Anais...Edinburgh, UK: Association for Computational Linguistics, 2011.

VILAIN, M. et al. A model-theoretic coreference scoring scheme. Proceedings of the 6th Message Understanding Conference (MUC-6). Anais...Los Altos, CA, EUA: Morgan Kaufmann, 1995. Disponível em: <http://acl.ldc.upenn.edu/M/M95/M95-1005.pdf>

VINCIARELLI, A. et al. Open challenges in modelling, analysis and synthesis of human behaviour in human–human and human–machine interactions. Cognitive Computation, v. 7, p. 397–413, 2015.

VINCZE, V.; NAGY T., I.; BEREND, G. Multiword Expressions and Named Entities in the Wiki50 Corpus. Proceedings of the International Conference Recent Advances in Natural Language Processing 2011. Anais...Hissar, Bulgaria: Association for Computational Linguistics, set. 2011. Disponível em: <https://aclanthology.org/R11-1040>

VINCZE, V.; NAGY T., I.; FARKAS, R. Identifying English and Hungarian Light Verb Constructions: A Contrastive Approach. Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Anais...Sofia, Bulgaria: Association for Computational Linguistics, ago. 2013. Disponível em: <https://aclanthology.org/P13-2046>

VINYALS, O.; LE, Q. A Neural Conversational Model., 2015. Disponível em: <https://doi.org/10.48550/arXiv.1506.05869>

VOGEL, L. H. Um olhar para além do verbo: os usos do olho na fala-em-interação. Universidade Federal do Rio Grande do Sul, 2018.

VOORHEES, E. M.; TICE, D. M. Building a Question Answering Test Collection. Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Anais...2000. Disponível em: <https://dl.acm.org/doi/10.1145/345508.345577>

VRANDEČIĆ, D.; KRÖTZSCH, M. Wikidata: a free collaborative knowledgebase. Communications of the ACM, v. 57, n. 10, p. 78–85, 2014.

WAGNER, J. et al. Dawn of the transformer era in speech emotion recognition: closing the valence gap. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023.

WAGNER, P.; MALISZ, Z.; KOPP, S. Gesture and speech in interaction: An overview. Speech CommunicationElsevier, 2014. Disponível em: <https://doi.org/10.1016/j.specom.2013.09.008>

WAGSTAFF, K. L. Machine learning that matters. Proceedings of the 29th International Coference on International Conference on Machine Learning. Anais...2012. Disponível em: <https://doi.org/10.48550/arXiv.1206.4656>

WALKER, M. A. et al. PARADISE: A Framework for Evaluating Spoken Dialogue Agents. 35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics. Anais...Madrid, Spain: Association for Computational Linguistics, jul. 1997. Disponível em: <https://aclanthology.org/P97-1035>

WALLIS, S. Completing Parsed Corpora. Em: ABEILLÉ, A. (Ed.). Treebanks: Building and Using Parsed Corpora. Dordrecht: Springer Netherlands, 2003. p. 61–71.

WALTER, E. (ED.). Cambridge Idioms Dictionary. 2. ed. Cambridge, UK: campress, 2006.

WANG, A. et al. GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding. Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP. Anais...Brussels, Belgium: Association for Computational Linguistics, nov. 2018. Disponível em: <https://aclanthology.org/W18-5446/>

WANG, A. et al. SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems. Advances in Neural Information Processing Systems, v. 32, p. 3261–3275, 2019.

WANG, C. et al. Covost: A diverse multilingual speech-to-text translation corpus. arXiv preprint arXiv:2002.01320, a2020.

WANG, C. et al. Voxpopuli: A large-scale multilingual speech corpus for representation learning, semi-supervised learning and interpretation. arXiv preprint arXiv:2101.00390, 2021.

WANG, C. et al. Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers. arXiv preprint arXiv:2301.02111, a2023.

WANG, C.; WU, A.; PINO, J. Covost 2 and massively multilingual speech-to-text translation. arXiv preprint arXiv:2007.10310, b2020.

WANG, W. Y.; GEORGILA, K. Automatic detection of unnatural word-level segments in unit-selection speech synthesis. 2011 IEEE Workshop on Automatic Speech Recognition & Understanding. Anais...IEEE, 2011.

WANG, Y. et al. Tacotron: A fully end-to-end text-to-speech synthesis model. arXiv preprint arXiv:1703.10135, 2017.

WANG, Y. et al. DSPM-NLG: A Dual Supervised Pre-trained Model for Few-shot Natural Language Generation in Task-oriented Dialogue System. Findings of the Association for Computational Linguistics: ACL 2023. Anais...b2023.

WANI, T. M. et al. A comprehensive review of speech emotion recognition systems. IEEE Access, v. 9, p. 47795–47814, 2021.

WATSON, D. The rhetoric and reality of anthropomorphism in artificial intelligence. Minds and Machines, v. 29, n. 3, p. 417–440, 2019.

WEN, T.-H. et al. Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems. Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Anais...: EMNLP’15.Lisbon, Portugal: Association for Computational Linguistics, 2015. Disponível em: <http://aclweb.org/anthology/D15-1199>

WEN, T.-H. et al. Multi-domain Neural Network Language Generation for Spoken Dialogue Systems. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Anais...: HLT-NAACL’16.San Diego, California: Association for Computational Linguistics, 2016. Disponível em: <https://aclanthology.info/pdf/N/N16/N16-1015.pdf>

WIELING, M.; RAWEE, J.; NOORD, G. VAN. Squib: Reproducibility in Computational Linguistics: Are We Willing to Share? Computational Linguistics, v. 44, n. 4, p. 641–649, dez. 2018.

WIGHTMAN, C. W.; OSTENDORF, M. Automatic recognition of prosodic phrases. [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, v. 1, p. 321–324, 1991.

WILKENS, R. et al. LexSubNC: A Dataset of Lexical Substitution for Nominal Compounds. Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017). Anais...Montpellier, France: 2017.

WILKS, Y. Is Word Sense Disambiguation Just One More NLP Task? Computers and the Humanities, v. 34, n. 1-2, p. 235–243, 2000.

WILLIAMS, I. et al. Contextual speech recognition in end-to-end neural network systems using beam search. 2018. Disponível em: <https://www.isca-speech.org/archive/Interspeech_2018/pdfs/2416.pdf>

WILLIAMS, J. D.; RAUX, A.; HENDERSON, M. The dialog state tracking challenge series: A review. Dialogue & Discourse, v. 7, n. 3, p. 4–33, 2016.

WILLRICH, R.; SANTOS, D. Avaliação no DIP. Linguamática, v. 15, n. 1, p. 69–87, 2023.

WILSON, T. P.; ZIMMERMAN, D. H. The structure of silence between turns in two-party conversation. Discourse processes, v. 9, n. 4, p. 375–390, 1986.

XIE, Z.; COHN, T.; LAU, J. H. The Next Chapter: A Study of Large Language Models in Storytelling., 2023. Disponível em: <https://arxiv.org/abs/2301.09790>

YANG, F.; HEEMAN, P. A.; KUN, A. L. An Investigation of Interruptions and Resumptions in Multi-Tasking Dialogues. Computational Linguistics, v. 37, n. 1, p. 75–104, mar. a2011.

YANG, J.-H. et al. Enriching Mandarin speech recognition by incorporating a hierarchical prosody model. 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Anais...b2011. Disponível em: <https://doi.org/10.1109/ICASSP.2011.5947492>

YANG, M. et al. Learning ASR pathways: A sparse multilingual ASR model., 2023. Disponível em: <https://arxiv.org/abs/2209.05735>

YANG, X. et al. An Entity-Mention Model for Coreference Resolution with Inductive Logic Programming. Proceeding of Association for Computational Linguistics. Anais...2008.

YAO, S. et al. ReAct: Synergizing Reasoning and Acting in Language Models., 2023. Disponível em: <https://arxiv.org/abs/2210.03629>

YAZDANI, M.; FARAHMAND, M.; HENDERSON, J. Learning Semantic Composition to Detect Non-compositionality of Multiword Expressions. Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Anais...Lisbon, Portugal: Association for Computational Linguistics, set. 2015. Disponível em: <https://aclanthology.org/D15-1201>

YEH, Y.-T.; ESKENAZI, M.; MEHRI, S. A Comprehensive Assessment of Dialog Evaluation Metrics. The First Workshop on Evaluations and Assessments of Neural Conversation Systems. Anais...Online: Association for Computational Linguistics, nov. 2021. Disponível em: <https://aclanthology.org/2021.eancs-1.3>

YI, J.; TAO, J. Self-attention Based Model for Punctuation Prediction Using Word and Speech Embeddings. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), p. 7270–7274, 2019.

YNGVE, V. H. Random generation of English sentences. [s.l.] Massachusetts Inst. of Technology, 1961.

YNGVE, V. H. On getting a word in edgewise. Papers from the sixth regional meeting Chicago Linguistic Society, April 16-18, 1970, Chicago Linguistic Society, Chicago. Anais...1970.

YU, J. et al. Choosing the content of textual summaries of large time-series data sets. Natural Language Engineering, v. 13, n. 1, p. 25–49, 2007.

ZAMPIERI, N.; ILLINA, I.; FOHR, D. Multiword Expression Features for Automatic Hate Speech Detection. (E. Métais et al., Eds.)Natural Language Processing and Information Systems - 26th International Conference on Applications of Natural Language to Information Systems, NLDB 2021, Saarbrücken, Germany, June 23-25, 2021, Proceedings. Anais...: Lecture Notes em Computer Science.Springer, 2021. Disponível em: <https://doi.org/10.1007/978-3-030-80599-9\_14>

ZANINELLO, A.; BIRCH, A. Multiword Expression aware Neural Machine Translation. Proceedings of the 12th Language Resources and Evaluation Conference. Anais...Marseille, France: European Language Resources Association, 2020. Disponível em: <https://aclanthology.org/2020.lrec-1.471>

ZE, H.; SENIOR, A.; SCHUSTER, M. Statistical parametric speech synthesis using deep neural networks. 2013 ieee international conference on acoustics, speech and signal processing. Anais...IEEE, 2013.

ZELASKO, P. et al. Punctuation Prediction Model for Conversational Speech. (B. Yegnanarayana, Ed.)Interspeech 2018, 19th Annual Conference of the International Speech Communication Association, Hyderabad, India, 2-6 September 2018. Anais...ISCA, 2018. Disponível em: <https://doi.org/10.21437/Interspeech.2018-1096>

ZEMAN, D. Reusable Tagset Conversion Using Tagset Drivers. Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC’08). Anais...Marrakech, Morocco: European Language Resources Association (ELRA), 2008. Disponível em: <http://www.lrec-conf.org/proceedings/lrec2008/pdf/66_paper.pdf>

ZEMAN, D.; RESNIK, P. Cross-Language Parser Adaptation between Related Languages. Proceedings of the IJCNLP-08 Workshop on NLP for Less Privileged Languages. Anais...2008. Disponível em: <https://aclanthology.org/I08-3008>

ZEN, H. et al. LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech. Proc. Interspeech 2019, p. 1526–1530, 2019.

ZEWDU, A.; YITAGESU, B. Part of speech tagging: a systematic review of deep learning and machine learning approaches. Journal of Big Data, v. 9, jan. 2022.

ZHANG, T. et al. BERTScore: Evaluating Text Generation with BERT. 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020. Anais...OpenReview.net, 2020. Disponível em: <https://openreview.net/forum?id=SkeHuCVFDr>

ZHANG, Z.; STRUBELL, E.; HOVY, E. A Survey of Active Learning for Natural Language Processing. (Y. Goldberg, Z. Kozareva, Y. Zhang, Eds.)Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. Anais...Abu Dhabi, United Arab Emirates: Association for Computational Linguistics, dez. 2022. Disponível em: <https://aclanthology.org/2022.emnlp-main.414/>

ZHAO, J. et al. Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers). Anais...New Orleans, Louisiana: Association for Computational Linguistics, jun. 2018. Disponível em: <https://aclanthology.org/N18-2003>

ZHOU, N. et al. CDGAN-BERT: Adversarial constraint and diversity discriminator for semi-supervised text classification. Knowledge-Based Systems, v. 284, p. 111291, 2024.

ZHU, X. et al. Introduction to Semi-Supervised Learning. [s.l.] Morgan; Claypool Publishers, 2009.

ZIN, K. K. Hidden Markov model with rule based approach for part of speech tagging of Myanmar language. International Conference on Intelligent Cloud Computing. Anais...2009. Disponível em: <https://api.semanticscholar.org/CorpusID:63473605>

ZOBEL, J. How reliable are the results of large-scale information retrieval experiments? Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval. Anais...ACM, 1998.