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Open Access

Improving Speaker Identification Performance Under the Shouted Talking Condition Using the Second-Order Hidden Markov Models

EURASIP Journal on Advances in Signal Processing20052005:375912

https://doi.org/10.1155/ASP.2005.482

Received: 13 June 2004

Published: 30 March 2005

Abstract

Speaker identification systems perform well under the neutral talking condition; however, they suffer sharp degradation under the shouted talking condition. In this paper, the second-order hidden Markov models (HMM2s) have been used to improve the recognition performance of isolated-word text-dependent speaker identification systems under the shouted talking condition. Our results show that HMM2s significantly improve the speaker identification performance compared to the first-order hidden Markov models (HMM1s). The average speaker identification performance under the shouted talking condition based on HMM1s is . On the other hand, the average speaker identification performance based on HMM2s is .

Keywords and phrases

first-order hidden Markov modelssecond-order hidden Markov modelsshouted talking conditionspeaker identification performance

Authors’ Affiliations

(1)
Electrical/Electronics and Computer Engineering Department, University of Sharjah, Sharjah, United Arab Emirates

Copyright

© Shahin 2005

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