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Topic-driven and knowledge-aware transformer for dialogue emotion detection
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Zhu, Lixing, Pergola, Gabriele, Gui, Lin, Zhou, Deyu and He, Yulan (2021) Topic-driven and knowledge-aware transformer for dialogue emotion detection. In: ACL 2021, Online, 2–4 Aug 2021. Published in: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language pp. 1571-1582.
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WRAP-topic-driven-knowledge-aware-transformer-dialogue-emotion-detection-He-2021.pdf - Accepted Version - Requires a PDF viewer. Download (2666Kb) | Preview |
Abstract
Emotion detection in dialogues is challenging as it often requires the identification of thematic topics underlying a conversation, the relevant commonsense knowledge, and the intricate transition patterns between the affective states. In this paper, we propose a Topic-Driven Knowledge-Aware Transformer to handle the challenges above. We firstly design a topic-augmented language model (LM) with an additional layer specialized for topic detection. The topic-augmented LM is then combined with commonsense statements derived from a knowledge base based on the dialogue contextual information. Finally, a transformer-based encoder-decoder architecture fuses the topical and commonsense information, and performs the emotion label sequence prediction. The model has been experimented on four datasets in dialogue emotion detection, demonstrating its superiority empirically over the existing state-of-the-art approaches. Quantitative and qualitative results show that the model can discover topics which help in distinguishing emotion categories.
| Item Type: | Conference Item (Paper) | |||||||||||||||||||||
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| Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > Q Science (General) Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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| Divisions: | Faculty of Science > Computer Science | |||||||||||||||||||||
| Library of Congress Subject Headings (LCSH): | Information retrieval, Knowledge representation (Information theory), Emotion recognition , Natural language processing (Computer science) , Computational linguistics, Sentiment analysis | |||||||||||||||||||||
| Journal or Publication Title: | Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language | |||||||||||||||||||||
| Publisher: | Association for Computational Linguistics | |||||||||||||||||||||
| Official Date: | 2021 | |||||||||||||||||||||
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| Page Range: | pp. 1571-1582 | |||||||||||||||||||||
| Status: | Peer Reviewed | |||||||||||||||||||||
| Publication Status: | Published | |||||||||||||||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||||||||||||||
| Copyright Holders: | ©2021 Association for Computational Linguistics | |||||||||||||||||||||
| RIOXX Funder/Project Grant: |
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| Conference Paper Type: | Paper | |||||||||||||||||||||
| Title of Event: | ACL 2021 | |||||||||||||||||||||
| Type of Event: | Conference | |||||||||||||||||||||
| Location of Event: | Online | |||||||||||||||||||||
| Date(s) of Event: | 2–4 Aug 2021 | |||||||||||||||||||||
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