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Published in:
2007 | OriginalPaper | Chapter
Maximum Likelihood and Maximum Mutual Information Training in Gender and Age Recognition System
Authors : Valiantsina Hubeika, Igor Szöke, Lukáš Burget, Jan Černocký
Published in: Text, Speech and Dialogue
Publisher: Springer Berlin Heidelberg
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Gender and age estimation based on Gaussian Mixture Models (GMM) is introduced. Telephone recordings from the Czech SpeechDat-East database are used as training and test data set. Mel-Frequency Cepstral Coefficients (MFCC) are extracted from the speech recordings. To estimate the GMMs’ parameters Maximum Likelihood (ML) training is applied. Consequently these estimations are used as the baseline for Maximum Mutual Information (MMI) training. Results achieved when employing both ML and MMI training are presented and discussed.