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Recent advances and challenges in task-oriented dialog systems

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Abstract

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.

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Authors and Affiliations

  1. Department of Computer Science & Technology, Tsinghua University, Beijing, 100084, China

    Zheng Zhang, Ryuichi Takanobu, Qi Zhu, MinLie Huang & XiaoYan Zhu

  2. Institute for Artificial Intelligence, Tsinghua University (THUAI), Beijing, 100084, China

    Zheng Zhang, Ryuichi Takanobu, Qi Zhu, MinLie Huang & XiaoYan Zhu

  3. Beijing National Research Center for Information Science & Technology, Beijing, 100084, China

    Zheng Zhang, Ryuichi Takanobu, Qi Zhu, MinLie Huang & XiaoYan Zhu

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  4. MinLie Huang
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Correspondence to MinLie Huang.

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This work was supported by the National Natural Science Foundation of China (Grant Nos. 61936010 and 61876096), and the National Key R&D Program of China (Grant No. 2018YFC0830200).

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Zhang, Z., Takanobu, R., Zhu, Q. et al. Recent advances and challenges in task-oriented dialog systems. Sci. China Technol. Sci. 63, 2011–2027 (2020). https://doi.org/10.1007/s11431-020-1692-3

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  • DOI: https://doi.org/10.1007/s11431-020-1692-3

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