Presentation | 2001/8/24 The SVD-based MLLR speaker adaption method Toyotsuna Imai, Kazumasa Yamamoto, Hiroshi Matsumoto, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In speaker adaption based on the MLLR framework, this paper proposes a SVD-based liner regression which can be applied to smaller regression classes and hence adapt HMMs to spectral dependent speaker differences. In this method, each row vector of a regression matrix is estimated by minimizing the norm under an effective rank based on a singular value decomposition(SVD) of the normal equation. This regressin transformation can be applied to any size of regression classes without ill-conditiones. This constrained MLLR is combined with a tree-based tying technique. Large vocabulary recognition tests show that the proposed method achieves 1% higher word accuracy than the conventional MLLR. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | MLLR / SVD / regresion class / effective rank / dictation system |
Paper # | SP2001-50 |
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Committee | SP |
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Conference Date | 2001/8/24(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Speech (SP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | The SVD-based MLLR speaker adaption method |
Sub Title (in English) | |
Keyword(1) | MLLR |
Keyword(2) | SVD |
Keyword(3) | regresion class |
Keyword(4) | effective rank |
Keyword(5) | dictation system |
1st Author's Name | Toyotsuna Imai |
1st Author's Affiliation | Faculty of Engineering, Shinshu University() |
2nd Author's Name | Kazumasa Yamamoto |
2nd Author's Affiliation | Faculty of Engineering, Shinshu University |
3rd Author's Name | Hiroshi Matsumoto |
3rd Author's Affiliation | Faculty of Engineering, Shinshu University |
Date | 2001/8/24 |
Paper # | SP2001-50 |
Volume (vol) | vol.101 |
Number (no) | 271 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |