This paper proposes an approach to improve speech understanding based on rescoring of N-best semantic hypotheses. In rescoring, probabilities produced by an understanding component are combined with additional probabilities derived from system beliefs. While a normal rescoring approach is to multiply or linearly interpolate with belief probabilities, this paper shows that probabilities from various sources are better combined using a nonlinear estimator. Using the proposed model together with a dialogue-state dependent semantic model shows a significant improvement when applying to a Thai interactive hotel reservation agent (TIRA), the first spoken dialogue system in Thai language.
Cite as: Wutiwiwatchai, C., Furui, S. (2004) Belief-based nonlinear rescoring in Thai speech understanding. Proc. Interspeech 2004, 2129-2133, doi: 10.21437/Interspeech.2004-226
@inproceedings{wutiwiwatchai04_interspeech,
author={Chai Wutiwiwatchai and Sadaoki Furui},
title={{Belief-based nonlinear rescoring in Thai speech understanding}},
year=2004,
booktitle={Proc. Interspeech 2004},
pages={2129--2133},
doi={10.21437/Interspeech.2004-226},
issn={2308-457X}
}