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Special Topic: Dialogue Act Recognition

Required Readings (for all students)

  1. Ali Ahmadvand, Jason Ingyu Choi, and Eugene Agichtein. Contextual Dialogue Act Classification for Open-Domain Conversational Agents. Proceedings of SIGIR, 2019.

Required Readings (for presenter(s) and rapporteur(s))
  1. Andreas Stolcke, Klaus Ries, Noah Coccaro, Elizabeth Shriberg, Rebecca Bates, Daniel Jurafsky, Paul Taylor, Rachel Martin, Marie Meteer, and Carol Van Ess-Dykema. Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational SpeechComputational Linguistics 26:3, 2000.
  2. Changwoo Chun, Daniel Rim, and Juhee Park. 2025. LLM ContextBridge: A Hybrid Approach for Intent and Dialogue Understanding in IVSR. In Proceedings of the 31st International Conference on Computational Linguistics: Industry Track, pages 794–806, Abu Dhabi, UAE. Association for Computational Linguistics.
  3. Wenjie Dong, Sirong Chen, and Yan Yang. 2025. ProTOD: Proactive Task-oriented Dialogue System Based on Large Language Model. In Proceedings of the 31st International Conference on Computational Linguistics, pages 9147–9164, Abu Dhabi, UAE. Association for Computational Linguistics.

Other Readings
  1. Norbert Reithinger. Some Experiments in Speech Act Prediction. In AAAI 95 Spring Symposium on Empirical Methods in Discourse Interpretation and Generation, 1995.
  2. CongKai Sun Louis-Philippe Morency Dialogue Act Recognition using Reweighted Speaker Adaptation Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), pages 118–125, Seoul, South Korea, 5-6 July 2012.
  3. Yang Liu, Kun Han, Zhao Tan, and Yun Lei. Using context information for dialog act classification in DNN framework. Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.
  4. Daniel Ortega and Ngoc Thang Vu. Neural-based context representation learning for dialog act classification. Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue (SIGDIAL), 2017.
  5. Chandrakant Bothe, Cornelius Weber, Sven Magg, and Stefan Wermter. A context-based approach for dialogue act recognition using simple recurrent neural networks. Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC), 2018.
  6. Viet-Trung Dang, Tianyu Zhao, Sei Ueno, Hirofumi Inaguma, and Tatsuya Kawahara. End-to-end speech-to-dialog-act recognition. Proceedings of Interspeech, 2020. Pierre Colombo, Emile Chapuis, Matteo Manica, Emmanuel Vignon, Giovanna Varni, and Chloe Clavel. Guiding attention in sequence-to-sequence act prediction models for dialogue. Proceedings of AAAI, 2020.
  7. Piotr Zelasko, Raghavendra Pappagari, and Najim Dehak. What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition. Transactions of the Association for Computational Linguistics, 9:1163-1179, 2021.