Special Topic: Dialogue Act Recognition
Required Readings
- 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.
Other Readings
- 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.
- 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.
- 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.
- 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.
- Ali Ahmadvand, Jason Ingyu Choi, and Eugene Agichtein. Contextual Dialogue Act Classification for Open-Domain Conversational Agents. Proceedings of SIGIR, 2019.