Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access
Seokhwan Kim, Mihail Eric, Karthik Gopalakrishnan, Behnam Hedayatnia, Yang Liu, Dilek Hakkani-Tur
Abstract
Most prior work on task-oriented dialogue systems are restricted to a limited coverage of domain APIs, while users oftentimes have domain related requests that are not covered by the APIs. In this paper, we propose to expand coverage of task-oriented dialogue systems by incorporating external unstructured knowledge sources. We define three sub-tasks: knowledge-seeking turn detection, knowledge selection, and knowledge-grounded response generation, which can be modeled individually or jointly. We introduce an augmented version of MultiWOZ 2.1, which includes new out-of-API-coverage turns and responses grounded on external knowledge sources. We present baselines for each sub-task using both conventional and neural approaches. Our experimental results demonstrate the need for further research in this direction to enable more informative conversational systems.- Anthology ID:
- 2020.sigdial-1.35
- Volume:
- Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue
- Month:
- July
- Year:
- 2020
- Address:
- 1st virtual meeting
- Venue:
- SIGDIAL
- SIG:
- SIGDIAL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 278–289
- URL:
- https://www.aclweb.org/anthology/2020.sigdial-1.35
- DOI:
- PDF:
- https://www.aclweb.org/anthology/2020.sigdial-1.35.pdf
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