Presentation 1997/12/11
Unsupervised Speaker Normalization by Canonical Correlation Analysis to Phoneme Representation Vectors
Miharu Sakuragi, Yasuo Ariki,
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Abstract(in English) Conventional speaker-independent HMMs ignore the speaker differences and collect speech data in an observation space. This causes a problem that the output probability distribution of the HMMs becomes vague so that, it deteriorates the recognition accuracy. To solve this problem, we construct the speaker subspace for an individual speaker and correlate them by o-space canonical correlation analysis between the standard speaker and input speaker. In order to remove the constraint that input speakers have to speak the same sentences as the standard speaker in the supervised normalization, we propose in this paper an unsupervised speaker normalization method which automatically segments the speech data into phoneme data by Viterbi decoding algorithm and then associates the mean feature vectors of phoneme data between speakers by o-space canonical correlation analysis.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) speaker-independent HMMs / supervised speaker normalization / unsupervised speaker normalization / Viterbe decoding algorithm
Paper # SP97-72
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Conference Information
Committee SP
Conference Date 1997/12/11(1days)
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Paper Information
Registration To Speech (SP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Unsupervised Speaker Normalization by Canonical Correlation Analysis to Phoneme Representation Vectors
Sub Title (in English)
Keyword(1) speaker-independent HMMs
Keyword(2) supervised speaker normalization
Keyword(3) unsupervised speaker normalization
Keyword(4) Viterbe decoding algorithm
1st Author's Name Miharu Sakuragi
1st Author's Affiliation Faculty of Science and Technology, Ryukoku University()
2nd Author's Name Yasuo Ariki
2nd Author's Affiliation Faculty of Science and Technology, Ryukoku University
Date 1997/12/11
Paper # SP97-72
Volume (vol) vol.97
Number (no) 441
Page pp.pp.-
#Pages 6
Date of Issue