End-to-End Personalized Humorous Response Generation in Untrimmed Multi-Role Dialogue System
文献类型：期刊论文
| 作者 | Yang, Qichuan2; He, Zhiqiang1,2,3; Zhan, Zhiqiang3; Li, Rang1; Lee, Yanwei1; Zhang, Yang1; Hu, Changjian1 |
| 刊名 | IEEE ACCESS
 |
| 出版日期 | 2019 |
| 卷号 | 7页码:94059-94071 |
| 关键词 | Dialogue generation multi-role conversation neural network reinforcement learning speaker prediction |
| ISSN号 | 2169-3536 |
| DOI | 10.1109/ACCESS.2019.2926830 |
| 英文摘要 | Multi-role dialogue is challenging in natural language processing (NLP), which needs not only to understand sentences but also to simulate interaction among roles. However, the existing methods assume that only two speakers are present in a conversation. In real life, this assumption is not always valid. More often, there are multiple speakers involved. To address this issue, we propose a multi-role interposition dialogue system (MIDS) that generates reasonable responses based on the dialogue context and next speaker prediction. The MIDS employs multiply role-defined encoders to understand each speaker and an independent sequence model to predict the next speaker. The independent sequence model also works as a controller to integrate encoders with weights. Then, an attention-enhanced decoder generates responses based on the dialogue context, speaker prediction, and integrated encoders. Moreover, with the help of unique speaker prediction, the MIDS is able to generate diverse responses and allow itself to join (interpose) the conversation when appropriate. Furthermore, a novel reward function and an updating policy of reinforcement learning (RL) are applied to the MIDS, which further enable MIDS the ability to write drama scripts. The experimental results demonstrate that the MIDS offers a significant improvement to the accuracy of speaker prediction and the reduction of response generation perplexity. It is also able to interact with users without cues during real-life online conversations and avoid meaningless conversation loops while generating scripts. This paper marks the first step toward multi-role humorous dialogue generation. |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000477867900029 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/4514]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Zhang, Yang |
| 作者单位 | 1.Lenovo Ltd, Res & Dev, Beijing 100094, Peoples R China 2.Beihang Univ, Sch Comp Sci & Engn, Beijing 100083, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yang, Qichuan,He, Zhiqiang,Zhan, Zhiqiang,et al. End-to-End Personalized Humorous Response Generation in Untrimmed Multi-Role Dialogue System[J]. IEEE ACCESS,2019,7:94059-94071. |
| APA | Yang, Qichuan.,He, Zhiqiang.,Zhan, Zhiqiang.,Li, Rang.,Lee, Yanwei.,...&Hu, Changjian.(2019).End-to-End Personalized Humorous Response Generation in Untrimmed Multi-Role Dialogue System.IEEE ACCESS,7,94059-94071. |
| MLA | Yang, Qichuan,et al."End-to-End Personalized Humorous Response Generation in Untrimmed Multi-Role Dialogue System".IEEE ACCESS 7(2019):94059-94071. |
入库方式： OAI收割
来源：计算技术研究所
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