Learning method of the dictionary as well as the hidden Markov model of speech recognition device and word components

摘要

PROBLEM TO BE SOLVED: To realize a high recognition performance in noisy environment in which pattern deformation is remarkably and to easily expand a vocabulary. ;SOLUTION: A phoneme dictionary learning section 21 generates noise superimposed voices from the clean voice data in a learning voice database 23 and noise data in a noise database 25 and learning of each phoneme dictionary in a phoneme dictionary storage section 15 is performed using the voices above. On the other had, a phoneme HMM learning section 22 generates noise superimposed voices from the clean voice data in an other leaning voice database 24 and the noise database in the database 25. Then, collating is performed by a phoneme degree of similarity computing section 13 between the time sequence of the feature parameters of the voices obtained by giving the voices to a voice analysis section 12 and the phoneme dictionary of the section 15 learned by the section 21 and the time sequence of the degree of similarity is obtained. Then, the learning of a phoneme HMM in a phoneme HMM storage section 16 is performed by using the time sequence of the degree of similarity.;COPYRIGHT: (C)1997,JPO