Multi-domain spoken language understanding with transfer learning

Authors:
Minwoo Jeong;Gary Geunbae Lee
Affiliations:
Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), San 31, Hyoja-Dong, Pohang 790-784, Republic of Korea;Department of Computer Science and Engineering, Pohang University of Science and Technology (POSTECH), San 31, Hyoja-Dong, Pohang 790-784, Republic of Korea
Venue:
Speech Communication
Year:
2009

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Abstract

This paper addresses the problem of multi-domain spoken language understanding (SLU) where domain detection and domain-dependent semantic tagging problems are combined. We present a transfer learning approach to the multi-domain SLU problem in which multiple domain-specific data sources can be incorporated. To implement multi-domain SLU with transfer learning, we introduce a triangular-chain structured model. This model effectively learns multiple domains in parallel, and allows use of domain-independent patterns among domains to create a better model for the target domain. We demonstrate that the proposed method outperforms baseline models on dialog data for multi-domain SLU problems.