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Speaker identification under background noise using features extracted from steady vowel regions
Author(s) -
Vuppala Anil Kumar,
Rao K. Sreenivasa
Publication year - 2013
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2357
Subject(s) - vowel , speech recognition , computer science , timit , noise (video) , identification (biology) , background noise , impulse response , speaker recognition , speaker identification , pattern recognition (psychology) , acoustics , artificial intelligence , mathematics , hidden markov model , physics , telecommunications , mathematical analysis , botany , image (mathematics) , biology
SUMMARY In this paper, we are exploring features extracted from steady vowel segments for improving the performance of speaker identification system under background noise. Steady vowel regions are produced by periodic impulse‐like excitation and they contain relatively high signal energy. Hence, speaker specific information present in steady vowel regions may be less affected by the noise. In this work, steady vowel regions are determined by using the knowledge of accurate vowel onset points and epochs. Speaker identification studies are carried out using TIMIT database for white and vehicle noises. Universal background model–Gaussian mixture model‐based modeling is explored for developing speaker models. Significant improvement in the performance of speaker identification is observed by using features extracted from steady vowel region in presence of noisy environments. Copyright © 2012 John Wiley & Sons, Ltd.