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作者:

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

收录:

EI Scopus

摘要:

This paper proposes a linear prediction-based part-defined auto-encoder (PAE) network to enhance speech signal. The PAE is a defined decoder or a defined encoder network, based on efficient learning algorithm or classical model. In this paper, the PAE utilizes AR-Wiener filter as decoder part, and the AR-Wiener filter is modified as a linear prediction (LP) model by incorporating the modified factor from residual signal. The parameters of line spectral frequency (LSF) of speech and noise and the Wiener filtering mask are utilized for training targets. Finally, the proposed the LP-based PAE is compared with the baseline method, namely the Wiener filtering mask-based DNN. The PESQ and STOI results of the LP-based PAE are better than baseline method at lower signal noise ratio (SNR) levels. © 2019 IEEE.

关键词:

Acoustic noise Audio signal processing Decoding Forecasting Learning algorithms Learning systems Signal encoding Signal to noise ratio Speech communication Speech enhancement

作者机构:

  • [ 1 ] [Cui, Zihao]Speech and Audio Signal Processing Laboratory, Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Bao, Changchun]Speech and Audio Signal Processing Laboratory, Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China

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ISSN: 1520-6149

年份: 2019

卷: 2019-May

页码: 6880-6884

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 2

ESI高被引论文在榜: 0 展开所有

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