A new speech recognition method based on VQ-distortion measure and HMM
Seiichi Nakagawa, Hajime Suzuki · IEEE International Conference on Acoustics Speech and Signal Processing · 1993
A speech recognition method which integrates a VQ (vector quantization)-distortion measure and a discrete HMM (hidden Markov model) is proposed. This VQ-distortion-based HMM uses a VQ-distortion measure at each state instead of the discrete output probability used by a discrete HMM. Although this method is regarded as a refined version of the VQ-distribution based recognition method proposed by D.K. Burton et al (IEEE Trans. vol. ASSP-33, no.4, p.837-49 of 1985), it is also considered as a special case of a mixtured distribution density HMM. The authors describe the relationship between the VQ-distortion-based HMM and conventional HMMs, and compare their speech recognition performance through experiments on speaker-dependent digit recognition. A recognition accuracy of 100% using the new method was obtained.>