CASIA OpenIR  > 多模态人工智能系统全国重点实验室  > 自然语言处理
Other Roles Matter! Enhancing Role-Oriented Dialogue Summarization via Role Interactions
Lin, Haitao1,2; Zhu, Junnan1,2; Xiang, Lu1,2; Zhou, Yu1,2,3; Zhang, Jiajun1,2; Zong, Chengqing1,2
2022-05
Conference Namethe 60th Annual Meeting of the Association for Computational Linguistics
Source PublicationProceedings of the 60th Annual Meeting of the Association for Computational Linguistics
Conference Date2022-05-22 - 2022-05-27
Conference PlaceDublin, Ireland
Abstract

Role-oriented dialogue summarization is to generate summaries for different roles in the dialogue, e.g., merchants and consumers. Existing methods handle this task by summarizing each role's content separately and thus are prone to ignore the information from other roles. However, we believe that other roles' content could benefit the quality of summaries, such as the omitted information mentioned by other roles. Therefore, we propose a novel role interaction enhanced method for role-oriented dialogue summarization. It adopts cross attention and decoder self-attention interactions to interactively acquire other roles' critical information. The cross attention interaction aims to select other roles' critical dialogue utterances, while the decoder self-attention interaction aims to obtain key information from other roles' summaries. Experimental results have shown that our proposed method significantly outperforms strong baselines on two public role-oriented dialogue summarization datasets. Extensive analyses have demonstrated that other roles' content could help generate summaries with more complete semantics and correct topic structures.

Indexed ByEI
Language英语
Sub direction classification自然语言处理
planning direction of the national heavy laboratory语音语言处理
Paper associated data
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/51971
Collection多模态人工智能系统全国重点实验室_自然语言处理
Corresponding AuthorZhou, Yu
Affiliation1.National Laboratory of Pattern Recognition, Institute of Automation, CAS, Beijing, China
2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
3.Fanyu AI Laboratory, Zhongke Fanyu Technology Co., Ltd, Beijing, China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Lin, Haitao,Zhu, Junnan,Xiang, Lu,et al. Other Roles Matter! Enhancing Role-Oriented Dialogue Summarization via Role Interactions[C],2022.
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