Abstract
Natural language understanding and dialog management are two integral components of interactive dialog systems. Previous research has used machine learning techniques to individually optimize these components, with different forms of direct and indirect supervision. We present an approach to integrate the learning of both a dialog strategy using reinforcement learning, and a semantic parser for robust natural language understanding, using only natural dialog interaction for supervision. Experimental results on a simulated task of robot instruction demonstrate that joint learning of both components improves dialog performance over learning either of these components alone.- Anthology ID:
- E17-1052
- Volume:
- Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 547–557
- Language:
- URL:
- https://aclanthology.org/E17-1052
- DOI:
- Cite (ACL):
- Aishwarya Padmakumar, Jesse Thomason, and Raymond J. Mooney. 2017. Integrated Learning of Dialog Strategies and Semantic Parsing. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 547–557, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Integrated Learning of Dialog Strategies and Semantic Parsing (Padmakumar et al., EACL 2017)
- PDF:
- https://preview.aclanthology.org/nodalida-main-page/E17-1052.pdf