An effective emotion tendency perception model in empathic dialogue.
The effectiveness of open-domain dialogue systems depends heavily on emotion. In dialogue systems, previous models primarily detected emotions by looking for emotional words embedded in sentences. However, they did not precisely quantify the association of all words with emotions, which has led to a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2023-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0282926 |
| _version_ | 1797843104520208384 |
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| author | Jiancu Chen Siyuan Yang Jiang Xiong Yiping Xiong |
| author_facet | Jiancu Chen Siyuan Yang Jiang Xiong Yiping Xiong |
| author_sort | Jiancu Chen |
| collection | DOAJ |
| description | The effectiveness of open-domain dialogue systems depends heavily on emotion. In dialogue systems, previous models primarily detected emotions by looking for emotional words embedded in sentences. However, they did not precisely quantify the association of all words with emotions, which has led to a certain bias. To overcome this issue, we propose an emotion tendency perception model. The model uses an emotion encoder to accurately quantify the emotional tendencies of all words. Meanwhile, it uses a shared fusion decoder to equip the decoder with the sentiment and semantic capabilities of the encoder. We conducted extensive evaluations on Empathetic Dialogue. Experimental results demonstrate its efficacy. Compared with the state of the art, our approach has distinctive advantages. |
| first_indexed | 2024-04-09T16:59:21Z |
| format | Article |
| id | doaj.art-55e10bc5295640eeae9a1c630ef3491a |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-09T16:59:21Z |
| publishDate | 2023-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-55e10bc5295640eeae9a1c630ef3491a2023-04-21T05:33:08ZengPublic Library of Science (PLoS)PLoS ONE1932-62032023-01-01183e028292610.1371/journal.pone.0282926An effective emotion tendency perception model in empathic dialogue.Jiancu ChenSiyuan YangJiang XiongYiping XiongThe effectiveness of open-domain dialogue systems depends heavily on emotion. In dialogue systems, previous models primarily detected emotions by looking for emotional words embedded in sentences. However, they did not precisely quantify the association of all words with emotions, which has led to a certain bias. To overcome this issue, we propose an emotion tendency perception model. The model uses an emotion encoder to accurately quantify the emotional tendencies of all words. Meanwhile, it uses a shared fusion decoder to equip the decoder with the sentiment and semantic capabilities of the encoder. We conducted extensive evaluations on Empathetic Dialogue. Experimental results demonstrate its efficacy. Compared with the state of the art, our approach has distinctive advantages.https://doi.org/10.1371/journal.pone.0282926 |
| spellingShingle | Jiancu Chen Siyuan Yang Jiang Xiong Yiping Xiong An effective emotion tendency perception model in empathic dialogue. PLoS ONE |
| title | An effective emotion tendency perception model in empathic dialogue. |
| title_full | An effective emotion tendency perception model in empathic dialogue. |
| title_fullStr | An effective emotion tendency perception model in empathic dialogue. |
| title_full_unstemmed | An effective emotion tendency perception model in empathic dialogue. |
| title_short | An effective emotion tendency perception model in empathic dialogue. |
| title_sort | effective emotion tendency perception model in empathic dialogue |
| url | https://doi.org/10.1371/journal.pone.0282926 |
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