Presentation 2007/7/19
A Speech Enhancement Framework Based on Noise Eigenspace Projection
Dongwen YING, Masashi UNOKI, Jianwu DANG,
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Abstract(in English) The performance of most speech enhancement algorithms declines under low-SNR conditions because of residual noise (or speech distortion) and the degradation of voice activity detector (VAD) performance. We therefore propose a speech enhancement approach based on noise eigenspace projection. When noisy speech is projected into the noise eigenspace, the noise energy is packed to a subspace consisting of dimensions with larger eigenvalues. This subspace is fairly dominated by noise. Removing the noise subspace can greatly reduce the noise at the cost of little speech loss. At the same time, the eigenspace dimensions having little noise are used to make a robust VAD. Using the proposed algorithm as a pre-processing block for conventional enhancement algorithms can efficiently reduce the residual noise under low-SNR conditions.
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Keyword(in English) speech enhancement / noise eigenspace / voice activity detection / Karhunen-Loeve transform
Paper # SP2007-42
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Committee SP
Conference Date 2007/7/19(1days)
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Registration To Speech (SP)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Speech Enhancement Framework Based on Noise Eigenspace Projection
Sub Title (in English)
Keyword(1) speech enhancement
Keyword(2) noise eigenspace
Keyword(3) voice activity detection
Keyword(4) Karhunen-Loeve transform
1st Author's Name Dongwen YING
1st Author's Affiliation School of Information Science, Japan Advanced Institute of Science and Technology()
2nd Author's Name Masashi UNOKI
2nd Author's Affiliation School of Information Science, Japan Advanced Institute of Science and Technology
3rd Author's Name Jianwu DANG
3rd Author's Affiliation School of Information Science, Japan Advanced Institute of Science and Technology
Date 2007/7/19
Paper # SP2007-42
Volume (vol) vol.107
Number (no) 165
Page pp.pp.-
#Pages 6
Date of Issue