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this paper a text-dependent speaker recognition method is presented by combining Mel frequency cepstrum coefficients (MFCC) and Euclidean distance. The robustness of this speaker identification method for different speaking language is analyzed in this paper. The speaker identification algorithm using English and Hindi Indian voice database (IVD) which contains sentences of data spoken is accomplished. An improvement in recognition rate is observed by using different windows and increasing the number of training voice samples. Accuracy upto 100% can be obtained for text-dependent speaker identification for different windows by using a short training and testing utterance about 4 seconds. KeywordsIdentification, MFCC, Euclidean distance classifier, Feature extraction and database.

A Comparative Analysis of Speaker Identification on English and Hindi Database