Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access

被引:0
作者
Kim, Seokhwan [1 ]
Eric, Mihail [1 ]
Gopalakrishnan, Karthik [1 ]
Hedayatnia, Behnam [1 ]
Liu, Yang [1 ]
Hakkani-Tur, Dilek [1 ]
机构
[1] Amazon Alexa AI, Sunnyvale, CA 94089 USA
来源
SIGDIAL 2020: 21ST ANNUAL MEETING OF THE SPECIAL INTEREST GROUP ON DISCOURSE AND DIALOGUE (SIGDIAL 2020) | 2020年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Most prior work on task-oriented dialogue systems are restricted to a limited coverage of domain APIs, while users oftentimes have domain related requests that are not covered by the APIs. In this paper, we propose to expand coverage of task-oriented dialogue systems by incorporating external unstructured knowledge sources. We define three sub-tasks: knowledge-seeking turn detection, knowledge selection, and knowledge-grounded response generation, which can be modeled individually or jointly. We introduce an augmented version of MultiWOZ 2.1, which includes new out-of-API-coverage turns and responses grounded on external knowledge sources. We present baselines for each sub-task using both conventional and neural approaches. Our experimental results demonstrate the need for further research in this direction to enable more informative conversational systems.
引用
收藏
页码:278 / 289
页数:12
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