On-line adaptation of the SCHMM parameters based on the segmental quasi-Bayes learning for speech recognition
Qiang Huo, Chorkin Chan, C.-H. Lee · IEEE Transactions on Speech and Audio Processing · 1996
On-line quasi-Bayes adaptation of the mixture coefficients and mean vectors in semicontinuous hidden Markov model (SCHMM) is studied. The viability of the proposed algorithm is confirmed and the related practical issues are addressed in a specific application of on-line speaker adaptation using a 26-word English alphabet vocabulary.