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作者:

Cui, Zihao (Cui, Zihao.) | Bao, Changchun (Bao, Changchun.) (学者:鲍长春)

收录:

EI SCIE

摘要:

In this letter, a novel weighted mean square error (WMSE) is proposed to improve the DNN-based mask approximation method for speech enhancement, in which the weighting is closely related to the power exponent about noisy spectrum amplitude (NSA) base. The power exponents 0 and 2 separately reflect ideal amplitude masking (IAM) without any clippings and the indirect mapping (IM) on short-time spectral amplitude (STSA), and it is highly related to the enhanced spectrum and the performance of the enhanced signal based on the tests. Also, the experimental results show that the outstanding weighting is the noisy spectrum base with the power exponent 1 for the phase-unaware masking and results in better harmonic structure restoration. The objective function with the WMSE on the NSA (WMSE-NSA) can averagely improve 0.1 on the test of perceptual evaluation of speech quality (PESQ) and 1.7% on the test of short-time objective intelligibility (STOI) compared with the MSE-based mask approximation methods. © 1994-2012 IEEE.

关键词:

Approximation theory Deep neural networks Mean square error Photomapping Speech enhancement Speech intelligibility

作者机构:

  • [ 1 ] [Cui, Zihao]Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Bao, Changchun]Beijing University of Technology, Beijing; 100124, China

通讯作者信息:

  • 鲍长春

    [bao, changchun]beijing university of technology, beijing; 100124, china

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来源 :

IEEE Signal Processing Letters

ISSN: 1070-9908

年份: 2021

卷: 28

页码: 618-622

3 . 9 0 0

JCR@2022

ESI学科: ENGINEERING;

ESI高被引阀值:9

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 4

ESI高被引论文在榜: 0 展开所有

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