A Novel Method for Speaker Independent Recognition Based on Hidden Markov Model

Abstract: In this paper, we address the speaker independent recognition of Chinese number speeches 0~9 based on HMM. Our former results of inside and outside testing achieved 92.5 % and 76.79 % respectively. To improve further the performance, two important features of speech; MFCC and cluster number of vector quantification, are unified together and evaluated on various values. The best performance achieve 96.2 % and 83.1 % on MFCC Number = 20 and VQ clustering number = 64