SPEAKER RECOGNITION USING GMM

摘要

The idea of the AUDIO SIGNAL PROCESSING (Speaker Recognition [4] Project) is to implement a recognizer using Matlab which can identify a person by processing his/her voice. The Matlab functions and scripts were all well documented and parameterized in order to be able to use them in the future. The basic goal of our project is to recognize and classify the speeches of different persons. This classification is mainly based on extracting several key features like Mel Frequency Cepstral Coefficients (MFCC [2]) from the speech signals of those persons by using the process of feature extraction using MATLAB. The above features may consists of pitch, amplitude, frequency etc. It can be achieved by using tools like MATLAB. Using a statistical model like Gaussian mixture model (GMM [6]) and features extracted from those speech signals we build a unique identity for each person who enrolled for speaker recognition [4]. Estimation and Maximization algorithm is used, An elegant and powerful method for finding the maximum likelihood solution for a model with latent variables, to test the later speeches against the database of all speakers who enrolled in the database.