Speaker recognition from speech using Gaussian mixture model (GMM) and (MFCC)

Abstract

This research presents a comprehensive presentation of speaker recognition technology, beginning with the basics of self-identification, extracting some features from the voice, models used, updates and current developments, and identifying methods for the Speaker Recognition System 'SRS'. first we extracted features from the speech signal and then we give them to the statistical model . This study We use GMM as statistical model to create a unique voice print for each identity Keywords (Speaker recognition , Feature extraction , Gaussian mixture model [GMM], Mel Frequency Cepstral Coefficients[MFCC].