MIME: MIMicking emotions for empathetic response generation
| Autor: | Deepanway Ghosal, Jiankun Lu, Pengfei Hong, Rada Mihalcea, Shanshan Peng, Navonil Majumder, Alexander Gelbukh, Soujanya Poria |
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| Předmět: |
FOS: Computer and information sciences
Response generation Computer Science - Computation and Language Computer science computer.internet_protocol media_common.quotation_subject 05 social sciences Empathy Negativity effect 010501 environmental sciences 01 natural sciences MIME 0502 economics and business Mimicry Relevance (information retrieval) 050207 economics Set (psychology) Computation and Language (cs.CL) computer 0105 earth and related environmental sciences media_common Cognitive psychology |
| Zdroj: | Scopus-Elsevier EMNLP (1) |
| Popis: | Current approaches to empathetic response generation view the set of emotions expressed in the input text as a flat structure, where all the emotions are treated uniformly. We argue that empathetic responses often mimic the emotion of the user to a varying degree, depending on its positivity or negativity and content. We show that the consideration of this polarity-based emotion clusters and emotional mimicry results in improved empathy and contextual relevance of the response as compared to the state-of-the-art. Also, we introduce stochasticity into the emotion mixture that yields emotionally more varied empathetic responses than the previous work. We demonstrate the importance of these factors to empathetic response generation using both automatic- and human-based evaluations. The implementation of MIME is publicly available at https://github.com/declare-lab/MIME. Comment: EMNLP 2020 |
| Databáze: | OpenAIRE |
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