Recent advances and challenges in task-oriented dialog systems

被引：68
|
作者：
Zhang, Zheng [1 ,2 ,3 ]
Takanobu, Ryuichi [1 ,2 ,3 ]
Zhu, Qi [1 ,2 ,3 ]
Huang, MinLie [1 ,2 ,3 ]
Zhu, XiaoYan [1 ,2 ,3 ]
机构：
[1] Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China
[2] Tsinghua Univ THUAI, Inst Artificial Intelligence, Beijing 100084, Peoples R China
[3] Beijing Natl Res Ctr Informat Sci & Technol, Beijing 100084, Peoples R China
来源：
SCIENCE CHINA-TECHNOLOGICAL SCIENCES | 2020年 / 63卷 / 10期
基金：
国家重点研发计划; 中国国家自然科学基金;
关键词：
task-oriented dialog systems; natural language understanding; dialog policy; dialog state tracking; natural language generation; USER SIMULATION; SEQUENCE; MODEL;
D O I：
10.1007/s11431-020-1692-3
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Due to the significance and value in human-computer interaction and natural language processing, task-oriented dialog systems are attracting more and more attention in both academic and industrial communities. In this paper, we survey recent advances and challenges in task-oriented dialog systems. We also discuss three critical topics for task-oriented dialog systems: (1) improving data efficiency to facilitate dialog modeling in low-resource settings, (2) modeling multi-turn dynamics for dialog policy learning to achieve better task-completion performance, and (3) integrating domain ontology knowledge into the dialog model. Besides, we review the recent progresses in dialog evaluation and some widely-used corpora. We believe that this survey, though incomplete, can shed a light on future research in task-oriented dialog systems.
引用
收藏
页码：2011 / 2027
页数：17
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