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CERG : Chinese Emotional Response Generator with Retrieval Method
https://tokushima-u.repo.nii.ac.jp/records/2009171
https://tokushima-u.repo.nii.ac.jp/records/200917195cfbd8d-1960-4780-8691-55e9e66ab5ea
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
research_2020_2616410.pdf (668 KB)
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| Item type | 文献 / Documents(1) | |||||||||||||
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| 公開日 | 2021-09-07 | |||||||||||||
| アクセス権 | ||||||||||||||
| アクセス権 | open access | |||||||||||||
| 資源タイプ | ||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||
| 資源タイプ | journal article | |||||||||||||
| 出版社版DOI | ||||||||||||||
| 識別子タイプ | DOI | |||||||||||||
| 関連識別子 | https://doi.org/10.34133/2020/2616410 | |||||||||||||
| 言語 | ja | |||||||||||||
| 関連名称 | 10.34133/2020/2616410 | |||||||||||||
| 出版タイプ | ||||||||||||||
| 出版タイプ | VoR | |||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||
| タイトル | ||||||||||||||
| タイトル | CERG : Chinese Emotional Response Generator with Retrieval Method | |||||||||||||
| 言語 | en | |||||||||||||
| 著者 |
Zhou, Yangyang
× Zhou, Yangyang
× 任, 福継
WEKO
401
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| 抄録 | ||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||
| 内容記述 | The dialogue system has always been one of the important topics in the domain of artificial intelligence. So far, most of the mature dialogue systems are task-oriented based, while non-task-oriented dialogue systems still have a lot of room for improvement. We propose a data-driven non-task-oriented dialogue generator “CERG” based on neural networks. This model has the emotion recognition capability and can generate corresponding responses. The data set we adopt comes from the NTCIR-14 STC-3 CECG subtask, which contains more than 1.7 million Chinese Weibo post-response pairs and 6 emotion categories. We try to concatenate the post and the response with the emotion, then mask the response part of the input text character by character to emulate the encoder-decoder framework. We use the improved transformer blocks as the core to build the model and add regularization methods to alleviate the problems of overcorrection and exposure bias. We introduce the retrieval method to the inference process to improve the semantic relevance of generated responses. The results of the manual evaluation show that our proposed model can make different responses to different emotions to improve the human-computer interaction experience. This model can be applied to lots of domains, such as automatic reply robots of social application. | |||||||||||||
| 言語 | en | |||||||||||||
| 書誌情報 |
en : Research 巻 2020, p. 2616410, 発行日 2020-09-07 |
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| 収録物ID | ||||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||||
| 収録物識別子 | 26395274 | |||||||||||||
| 収録物ID | ||||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||||
| 収録物識別子 | 20965168 | |||||||||||||
| 出版者 | ||||||||||||||
| 出版者 | Science and Technology Review Publishing House | |||||||||||||
| 言語 | en | |||||||||||||
| 出版者 | ||||||||||||||
| 出版者 | American Association for the Advancement of Science | |||||||||||||
| 言語 | en | |||||||||||||
| 出版者 | ||||||||||||||
| 出版者 | China Association for Science and Technology | |||||||||||||
| 言語 | en | |||||||||||||
| 権利情報 | ||||||||||||||
| 言語 | en | |||||||||||||
| 権利情報 | Distributed under a Creative Commons Attribution License (CC BY 4.0). | |||||||||||||
| EID | ||||||||||||||
| 識別子 | 372538 | |||||||||||||
| 識別子タイプ | URI | |||||||||||||
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| 言語 | eng | |||||||||||||
