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A novel method for text-independent speaker identification using MFCC and GMM

Publication Type : Conference Paper

Publisher : ICALIP 2010 - 2010 International Conference on Audio, Language and Image Processing, Proceedings

Source : ICALIP 2010 - 2010 International Conference on Audio, Language and Image Processing, Proceedings, Shanghai, p.292-296 (2010)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-79851488862&partnerID=40&md5=7691cfa10b3e47d231bb7a0f9a793440

ISBN : 9781424458653

Keywords : decision making, Decision making process, Experimental studies, Gaussian mixture modeling, Gaussian mixtures, Image processing, Imaging systems, Language environment, Likelihood ratios, Loudspeakers, Maximum likelihood, Mel-frequency cepstral coefficients, Novel methods, Recognition rates, Speaker identification, Speaker model, Speaker recognition, Speaker verification, Speech duration, Speech feature parameter, Speech features, Speech recognition, Text-independent speaker identification, Time duration

Campus : Amritapuri

School : School of Biotechnology

Department : biotechnology

Year : 2010

Abstract : The area of speaker recognition is concerned with extracting the identity of the person speaking. Speaker recognition can be classified into speaker identification and speaker verification. Speaker identification can be Text-Independent or Text-Dependent. In this paper we lay emphasis on text-Independent speaker identification system where we adopted Mel-Frequency Cepstral Coefficients (MFCC) as the speaker speech feature parameters in the system and the concept of Gaussian Mixture Modeling (GMM) for modeling the extracted speech feature. We used the Maximum Likelihood Ratio Detector algorithm for the decision making process. The experimental study has been performed for various speech time duration and several languages and was conducted around MATLAB 7 language environment. Gaussian mixture speaker model attains high recognition rate for various speech durations. ©2010 IEEE.

Cite this Research Publication : M. S. Sinith, Salim, A., G. K, S., S. V, N. K., and Soman, V., “A novel method for text-independent speaker identification using MFCC and GMM”, in ICALIP 2010 - 2010 International Conference on Audio, Language and Image Processing, Proceedings, Shanghai, 2010, pp. 292-296.

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