Multimedia utilization of non-computerized disguised voice and acoustic similarity measurement

Abstract

In this paper, an identification of a speaker for multimedia application under non-electronically disguised voice is performed. In non-electronically disguised voice under physical variation of speech, it is a difficult task to identify the speaker in speech signal processing application area. Due to changes in the frequency spectrum of the speech signal during non- electronic disguising, some methods like Mel-frequency cepstrum coefficients (MFCC), delta Mel-frequency cepstrum coefficients (ΔMFCC) and double delta Mel-frequency cepstrum coefficients (ΔΔMFCC) are used to specify the frequencies spectral property. A new algorithm developed, based on acoustic feature extraction by MFCC technique of text-dependent speech signal of all speaker’s and changed their speech by six physical variation methods. The acoustic features which include the correlation coefficients and the mean value are extracted by the MFCC, ΔMFCC and ΔΔMFCC feature extraction method. Thereafter, different classifiers based on feature extraction are used to classify the non-electronically disguised voice and normal voice.