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://preview.aclanthology.org/add_missing_videos/2024.yrrsds-1.13/
- DOI:
- 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 2024)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2024.yrrsds-1.13.pdf