Speaker normalization equipment, speaker adaptation apparatus and speech recognition apparatus

摘要

PROBLEM TO BE SOLVED: To provide the speaker normalizing device, the speaker adaptive device and the speech recognizer while improving the estimating precision of adaptive parameters compared with the conventional ones and improving the speech recognition rate. SOLUTION: A speaker normalization control section 20 computes the transformation coefficient, which includes a transformation matrix and a constant term vector for every speaker. The matrix transforms an average vector based on a multiple regression mapping model employing a maximum likelihood linear regression method against an initial hidden Markov model(HMM) 31 based on the voice data that depend on plural speakers. The constant term vector is subtracted from the voice data, normalized voice data are computed, an initial HMM is learned and the HMM, which is speaker normalized, is obtained. A speaker adaptive control section 21 computes the transformation coefficient against a speaker normalized HMM 33 based on speaker adaptive learning data. Then, the transformation coefficient for the transformation based on the model, which is made speaker adaptive by a MAP estimating method, is computed and linear transformation processed to compute the average vector of the HMM after the speaker adaptive process. Then, an HMM 11, which is made speaker adaptive, is obtained.