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Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation

文献类型：期刊论文

作者Zhang, Yingying1,3; Fang, Quan3,4; Qian, Shengsheng3,4; Xu, Changsheng1,2,3
刊名ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
出版日期2020-07-01
卷号11期号:4页码:20
关键词Dialogue system co-attention adversarial learning external knowledge
ISSN号2157-6904
DOI10.1145/3384675
通讯作者Zhang, Yingying(zhangyingying2017@ia.ac.cn)
英文摘要Natural language generation has become a fundamental task in dialogue systems. RNN-based natural response generation methods encode the dialogue context and decode it into a response. However, they tend to generate dull and simple responses. In this article, we propose a novel framework, called KAWA-DRG (Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation) to model conversation-specific external knowledge and the importance variances of dialogue context in a unified adversarial encoder-decoder learning framework. In KAWA-DRG, a co-attention mechanism attends to important parts within and among context utterances with word-utterance-level attention. Prior knowledge is integrated into the conditional Wasserstein auto-encoder for learning the latent variable space. The posterior and prior distribution of latent variables are generated and trained through adversarial learning. We evaluate our model on Switchboard, DailyDialog, In-Car Assistant, and Ubuntu Dialogue Corpus. Experimental results show that KAWA-DRG outperforms the existing methods.
资助项目National Key Research and Development Program of China[2017YFB1002804] ; National Natural Science Foundation of China[61720106006] ; National Natural Science Foundation of China[61572503] ; National Natural Science Foundation of China[61802405] ; National Natural Science Foundation of China[61872424] ; National Natural Science Foundation of China[61702509] ; National Natural Science Foundation of China[61832002] ; National Natural Science Foundation of China[61936005] ; National Natural Science Foundation of China[U1705262] ; Key Research Program of Frontier Sciences, CAS[QYZDJ-SSW-JSC039] ; K.C. Wong Education Foundation
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000583127700002
出版者ASSOC COMPUTING MACHINERY
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China ; Key Research Program of Frontier Sciences, CAS ; K.C. Wong Education Foundation
源URL[http://ir.ia.ac.cn/handle/173211/41805]  
专题自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
通讯作者Zhang, Yingying
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, 95 ZhongGuanChun East Rd, Beijing 100190, Peoples R China
2.Peng Cheng Lab, 95 ZhongGuanChun East Rd, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing, Peoples R China
4.Univ Chinese Acad Sci, 95 ZhongGuanChun East Rd, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Yingying,Fang, Quan,Qian, Shengsheng,et al. Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation[J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,2020,11(4):20.
APA Zhang, Yingying,Fang, Quan,Qian, Shengsheng,&Xu, Changsheng.(2020).Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation.ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,11(4),20.
MLA Zhang, Yingying,et al."Knowledge-aware Attentive Wasserstein Adversarial Dialogue Response Generation".ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 11.4(2020):20.

入库方式： OAI收割

来源：自动化研究所

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