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.
Bibliographic reference. Blackburn, C. S. / Young, S. J. (1995): "Towards improved speech recognition using a speech production model", In EUROSPEECH-1995, 1623-1626.