Considerable improvement in the performance of continuous speech recognition systems, particularly those based on Hidden Markov Models (HMMs), has been shown in recent years. Nevertheless a number of unsolved problems remain which limit this progress, including the successful modelling of co-articulation and the identification of out of vocabulary utterances. One possible solution is to re-synthesise speech from the N-best time-aligned phonemic transcriptions produced by an HMM, and re-score this list based on a spectral comparison between the original and re-synthesised speech frames. In this paper a novel speech production model (SPM) suitable for use in such a system is introduced, and preliminary re-scoring results are presented.
Cite as: Blackburn, C.S., Young, S.J. (1995) Towards improved speech recognition using a speech production model. Proc. 4th European Conference on Speech Communication and Technology (Eurospeech 1995), 1623-1626, doi: 10.21437/Eurospeech.1995-393
@inproceedings{blackburn95_eurospeech,
author={C. S. Blackburn and S. J. Young},
title={{Towards improved speech recognition using a speech production model}},
year=1995,
booktitle={Proc. 4th European Conference on Speech Communication and Technology (Eurospeech 1995)},
pages={1623--1626},
doi={10.21437/Eurospeech.1995-393}
}