ISSN 0021-3454 (print version)
ISSN 2500-0381 (online version)
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12
Issue
vol 59 / DECEMBER, 2016
Article
UDC 519.86

DETERMINATION OF CHANNEL-INDEPENDENT INFORMATION INDICATORS

V. V. Kiselyov
Speech Technology Ltd., Minsk; Director


A. V. Tkachenia
Speech Technology Ltd., Minsk; Junior Scientist


M. V. Khitrov
STC Ltd., St. Petersburg; ITMO University, Department of Speech Information Systems; General Director; Head of the Department


Abstract. Information indicators of speech are analyzed for creation of channel-independent feature space aimed at improvement of speaker recognition system efficiency. For the problem of determination of similarity between several audio recordings, the optimal set of channel-independent information feature vectors is determined experimentally with the use of dynamic time warping.
Keywords: speech analysis, machine learning, feature selection, mel-frequency cepstral coefficients, dynamic time warping