•  
  •  
 

International Journal of Electronics and Electical Engineering

Abstract

The idea of the Speaker Identification is to implement a recognizer using Matlab which can identify a person by processing his/her voice. The basic goal of the paper is to classify and recognize the speeches of different persons. This classification is mainly based on extracting several key features like Mel Frequency Cepstral Coefficients (MFCC) 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. Using a statistical model like Gaussian mixture model (GMM) and features extracted from those speech signals we build a unique identity for each person who enrolled for speaker recognition. There is an elegant and powerful method for finding the maximum likelihood and that method is called Expectation and Maximization algorithm. The performance of the technique has been measured by three parameters: Number of Speakers in Database, Number of Persons Tested and the % Error.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.