Emp-RFT: Empathetic Response Generation via Recognizing Feature Transitions between Utterances

Anonymous

Paper Link: https://openreview.net/forum?id=1Q_Q7V9AZnF

Paper Type: Long paper (up to eight pages of content + unlimited references and appendices)

Abstract: Each utterance in multi-turn empathetic dialogues has features such as emotion, keywords, and utterance-level meaning. Feature transitions between utterances occur naturally. However, existing approaches fail to perceive the transitions because they extract features for the context at the coarse-grained level. To solve the above issue, we propose a novel approach of recognizing feature transitions between utterances, which helps understand the dialogue flow and better grasp the features of utterance that needs attention. Also, we introduce a response generation strategy to help focus on emotion and keywords related to appropriate features when generating responses. Experimental results show that our approach outperforms baselines and especially, achieves significant improvements on multi-turn dialogues.

Copyright Consent Signature (type Name Or NA If Not Transferrable): Wongyu Kim

Copyright Consent Name And Address: Yonsei University / 50, Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea

Presentation Mode: This paper will be presented in person in Seattle