Towards Robust and Multilingual Task-Oriented Dialogue Systems

Atsumoto Ohashi


Abstract
In this position paper, I present my research interests regarding the field of task-oriented dialogue systems. My work focuses on two main aspects: optimizing the task completion ability of dialogue systems using reinforcement learning, and developing language resources and exploring multilinguality to support the advancement of dialogue systems across different languages. I discuss the limitations of current approaches in achieving robust task completion performance and propose a novel optimization approach called Post-Processing Networks. Furthermore, I highlight the importance of multilingual dialogue datasets and describe our work on constructing JMultiWOZ, the first large-scale Japanese task-oriented dialogue dataset.
Anthology ID:
2024.yrrsds-1.13
Volume:
Proceedings of the 20th Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems
Month:
September
Year:
2024
Address:
Kyoto, Japan
Editors:
Koji Inoue, Yahui Fu, Agnes Axelsson, Atsumoto Ohashi, Brielen Madureira, Yuki Zenimoto, Biswesh Mohapatra, Armand Stricker, Sopan Khosla
Venues:
YRRSDS | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
35–36
Language:
URL:
https://aclanthology.org/2024.yrrsds-1.13
DOI:
Bibkey:
Cite (ACL):
Atsumoto Ohashi. 2024. Towards Robust and Multilingual Task-Oriented Dialogue Systems. In Proceedings of the 20th Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems, pages 35–36, Kyoto, Japan. Association for Computational Linguistics.
Cite (Informal):
Towards Robust and Multilingual Task-Oriented Dialogue Systems (Ohashi, YRRSDS-WS 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.yrrsds-1.13.pdf