Presentation 2012/12/13
A Study on Unsupervised Speaker Adaptation for Feature Enhancement
DUYNGUYEN DUC, TAKUYA YOSHIOKA, NOBUAKI MINEMATSU, KEIKICHI HIROSE,
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Abstract(in English) Speech recognition has been an active research area for many years, and nowadays, it is being used in many practical applications. However, the recognition performance is often seriously degraded by noise and reverberation present in recording environments. One promising approach to solve this problem is feature enhancement, which attempts to restore clean feature vectors using a GMM of clean speech. Mean-while, in many recent applications including those to mobile devices, it is easy to collect target user's speech data recorded in various environments. However, how to exploit these data for improving the performance of a speech recognizer that performs feature enhancement is an open question. This study experimentally compares different methods for combining MAP adaptation of the clean speech GMM and MLLR adaptation of the recognizer's acoustic model.
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Keyword(in English) Feature enhancement / VTS / MAP adaptation / MLLR adaptation / Speaker adaptation
Paper # SLP-94
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Conference Information
Committee SP
Conference Date 2012/12/13(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) A Study on Unsupervised Speaker Adaptation for Feature Enhancement
Sub Title (in English)
Keyword(1) Feature enhancement
Keyword(2) VTS
Keyword(3) MAP adaptation
Keyword(4) MLLR adaptation
Keyword(5) Speaker adaptation
1st Author's Name DUYNGUYEN DUC
1st Author's Affiliation NTT Communication Science Laboratories,NTT Corporation:Graduate School of Information and Technology The University of Tokyo()
2nd Author's Name TAKUYA YOSHIOKA
2nd Author's Affiliation NTT Communication Science Laboratories,NTT Corporation
3rd Author's Name NOBUAKI MINEMATSU
3rd Author's Affiliation Graduate School of Information and Technology The University of Tokyo
4th Author's Name KEIKICHI HIROSE
4th Author's Affiliation Graduate School of Information and Technology The University of Tokyo
Date 2012/12/13
Paper # SLP-94
Volume (vol) vol.112
Number (no) 369
Page pp.pp.-
#Pages 6
Date of Issue