“Do you follow me?”: A Survey of Recent Approaches in Dialogue State Tracking

Léo Jacqmin, Lina M. Rojas Barahona, Benoit Favre


Abstract
While communicating with a user, a task-oriented dialogue system has to track the user’s needs at each turn according to the conversation history. This process called dialogue state tracking (DST) is crucial because it directly informs the downstream dialogue policy. DST has received a lot of interest in recent years with the text-to-text paradigm emerging as the favored approach. In this review paper, we first present the task and its associated datasets. Then, considering a large number of recent publications, we identify highlights and advances of research in 2021-2022. Although neural approaches have enabled significant progress, we argue that some critical aspects of dialogue systems such as generalizability are still underexplored. To motivate future studies, we propose several research avenues.
Anthology ID:
2022.sigdial-1.33
Volume:
Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue
Month:
September
Year:
2022
Address:
Edinburgh, UK
Editors:
Oliver Lemon, Dilek Hakkani-Tur, Junyi Jessy Li, Arash Ashrafzadeh, Daniel Hernández Garcia, Malihe Alikhani, David Vandyke, Ondřej Dušek
Venue:
SIGDIAL
SIG:
SIGDIAL
Publisher:
Association for Computational Linguistics
Note:
Pages:
336–350
Language:
URL:
https://aclanthology.org/2022.sigdial-1.33
DOI:
10.18653/v1/2022.sigdial-1.33
Bibkey:
Cite (ACL):
Léo Jacqmin, Lina M. Rojas Barahona, and Benoit Favre. 2022. “Do you follow me?”: A Survey of Recent Approaches in Dialogue State Tracking. In Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 336–350, Edinburgh, UK. Association for Computational Linguistics.
Cite (Informal):
“Do you follow me?”: A Survey of Recent Approaches in Dialogue State Tracking (Jacqmin et al., SIGDIAL 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.sigdial-1.33.pdf
Video:
 https://youtu.be/8ZXMHsYDlCQ
Data
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