Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

4-2021

Abstract

Multi-domain dialogue state tracking (DST) is a critical component for monitoring user goals during the course of an interaction. Existing approaches have relied on dialogue history indiscriminately or updated on the most recent turns incrementally. However, in spite of modeling it based on fixed ontology or open vocabulary, the former setting violates the interactive and progressing nature of dialogue, while the later easily gets affected by the error accumulation conundrum. Here, we propose a Recursive Inference mechanism (ReInf) to resolve DST in multi-domain scenarios that call for more robust and accurate tracking capability. Specifically, our agent reversely reviews the dialogue history until the agent has pinpointed sufficient turns confidently for slot value prediction. It also recursively factors in potential dependencies among domains and slots to further solve the co-reference and value sharing problems. The quantitative and qualitative experimental results on the MultiWOZ 2.1 corpus demonstrate that the proposed ReInf not only outperforms the state-of-the-art methods, but also achieves reasonable turn reference and interpretable slot co-reference.

Keywords

Dialogue state tracking, Recursive inference

Discipline

Artificial Intelligence and Robotics

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the 2021 World Wide Web Conference, Ljubljana, Slovenia, April 19 - 23

First Page

2568

Last Page

2577

ISBN

9781450383127

Identifier

10.1145/3442381.3450134

Publisher

Association for Computing Machinery

City or Country

United States

Additional URL

https://doi.org/10.1145/3442381.3450134

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