Presentation 2014-01-23
Fundamental study of speaker identification by the peripheral auditory model and deep neural network
Masanori MORISE, Kenji OZAWA,
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Abstract(in English) In the recognition of linguistic information, the acoustic features for explaining the comprehensive structure of the power spectrum are important because they do not depend on the individuality. Other acoustic features would be important to deal with the speaker identification and emotion. Mel-frequency cepstrum coefficients (MFCC) has been used as one of the effective acoustic features for recognizing not only linguistic information, but also the speaker identification. However, MFCC is specialized to recognize the linguistic information. In this research, we focused on using the deep neural network (DNN) for speaker identification, and examined the acoustic features for achieving the high performance. The proposed method uses the output of peripheral auditory model as the input of DNN. An evaluation with 1480 speech samples uttered by two males and two females was carried out, and the effectiveness of the proposed method was discussed based on the result.
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Keyword(in English) Speech analysis / speaker identification / peripheral auditory model / deep neural network
Paper # SP2013-97
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Committee SP
Conference Date 2014/1/16(1days)
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Registration To Speech (SP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Fundamental study of speaker identification by the peripheral auditory model and deep neural network
Sub Title (in English)
Keyword(1) Speech analysis
Keyword(2) speaker identification
Keyword(3) peripheral auditory model
Keyword(4) deep neural network
1st Author's Name Masanori MORISE
1st Author's Affiliation Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi()
2nd Author's Name Kenji OZAWA
2nd Author's Affiliation Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi
Date 2014-01-23
Paper # SP2013-97
Volume (vol) vol.113
Number (no) 404
Page pp.pp.-
#Pages 6
Date of Issue