Presentation | 2008-01-25 Noisy Speech Recognition Using Spectral Subtraction with an Adaptive SNR Method Jun TOYAMA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Spectral Subtraction method is well known the effective reduction method for corrupted speech with stationary noise. But, real noise is not always stationary. A noise reduction method dealing with variations of noise power using a optimization method is proposed. Additionally, computational costs are improved by increasing computation that does not depend on acoustic models , when Taylor expansion is applied to irrational expressions in the criterion function. As results form the evaluation using AURORA-2J, the propose method without using Taylor expansion achieves word accuracies of 23% 77% and 97% for clean training condition under the SNR condition 0dB, 10dB and 20dB, respectively. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Spectral Subtraction method / Variation of Noise Power / Optimize Problem / Taylor Expansion |
Paper # | TL2007-74,SP2007-169,WIT2007-74 |
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Conference Information | |
Committee | WIT |
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Conference Date | 2008/1/18(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Well-being Information Technology(WIT) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Noisy Speech Recognition Using Spectral Subtraction with an Adaptive SNR Method |
Sub Title (in English) | |
Keyword(1) | Spectral Subtraction method |
Keyword(2) | Variation of Noise Power |
Keyword(3) | Optimize Problem |
Keyword(4) | Taylor Expansion |
1st Author's Name | Jun TOYAMA |
1st Author's Affiliation | Graduate School of Information Science and Technology, Hokkaido University() |
Date | 2008-01-25 |
Paper # | TL2007-74,SP2007-169,WIT2007-74 |
Volume (vol) | vol.107 |
Number (no) | 437 |
Page | pp.pp.- |
#Pages | 6 |
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