Speaker‐independent consonant recognition by integrating discriminant analysis and hmm

A new consonant recognition method is proposed which integrates two stochastic methods: discriminant analysis and HMM. Discriminant analysis is effective in analyzing local patterns but it assumes precise detection of reference points. HMM is able to extract the overall dynamic features and needs no explicit segmentation of speech. However, it lacks the ability to discriminate between similar consonants. The method herein constructs HMM with discriminant analysis front end and recognizes consonants by combining the score obtained by discriminant analysis and that by HMM. For all the Japanese consonants, this integrated method achieved the recognition rate of 92.1 percent, which is higher by 5 to 15 percent than the case using either of the two methods alone.