Speaker verification using Gaussian Mixture Model

In this paper, speaker verification system using Gaussian Mixture Model (GMM) is proposed. The proposed system consists of pre-processing, feature extraction, modelling and classification stage. The pre-processing is used to remove silent part of signal to reduce computational complexity. Pitch frequency and Mel Frequency Cepstral Coefficients(MFCC)are used as a feature vector for speaker verification system. Modelling is done using different combination of Gaussian mixture models. Simple distance measures are used for the classification between reference and the test signal.