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Voice Recognition Technique using Guassian Mixture Model

Anagha Girme, Nivedita Mahato, Sucheta Manve, Abhijeet Banubakode


This paper gives us some of the important information about the methods used for voice recognition system. Voice recognition is the identification of person with the help of characteristic of voice. Voice recognition has scope ranging from access control to forensics. In this system we are able to identify the speaker as well as verification of the speaker take place using feature extraction and feature matching technique using GMM. In this work the features of voice of the person are extracted with the help of Mel-Frequency Cepstral Coefficient (MFCC) and Subband based Cepstral Parameter (SBC). Hence the accuracy of speaker recognition increases giving speaker a more flexible system .In the experimental result SBC is more accurate than MFCC.

Cite this Article
Anagha Girme, Nivedita Mahato, Sucheta Manve, Abhijeet Banubakode. Voice Recognition Technique Using Guassian Mixture Model. Journal of Artificial Intelligence Research & Advances. 2015; 2(2): 12–15p.


Mel-Frequency cepstral coefficient (MFCC), guassian mixture model (GMM), subband based cepstral parameter (SBC), feature extraction, speaker identification, speaker verification

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