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Abstract:
This paper presents a method of features extraction in Speaker Recognition. This method divides voice signal into two parts based on the MPEG Psychological Model I, and processes them respectively. And then we analyze the extracted MFCC parameters, and compare the partition of frequency-band between Mel-spaced filter group and wavelet packet decomposition. We extract the coefficients by Wavelet Package Transform (called 'WPTC') as diagnostic parameters used in the Speaker Recognition. The results of experiments indicated that it perform well than MFCC while using the WPTC based on MPEG-1. © 2008 IEEE.
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Year: 2008
Volume: 1
Page: 1048-1052
Language: English
Cited Count:
WoS CC Cited Count: 0
SCOPUS Cited Count: 2
ESI Highly Cited Papers on the List: 0 Unfold All
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30 Days PV: 5
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