Towards improved speech recognition using a speech production model
C. S. Blackburn, S. J. Young · 1995
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. 1. INTRODUCTION The application of speech production models to the task of automatic speech recognition is a relatively new area of research which has attracted increasing interest over the past few years [10]. The basic operation of such a combined syste...