Study of widely linear multichannel wiener filter for binaural noise reduction

Xin Leng, Jingdong Chen, Israel Cohen, Jacob Benesty

科研成果: 书/报告/会议事项章节会议稿件同行评审

4 引用 (Scopus)

摘要

In this paper, we study the binaural noise-reduction problem using an array of microphones. The widely linear (WL) framework in the short-time-Fourier-transform (STFT) domain is adopted. In such a framework, the microphone array signals and binaural outputs are first merged into complex signals. These complex signals are subsequently transformed into the STFT domain. The WL estimation theory is then applied in STFT subbands with interband correlation to form the optimal WL Wiener filter, which exploits the noncircular properties of the input complex signals to achieve noise reduction and meanwhile to preserve the sound spatial realism. Finally, the time-domain binaural output is reconstructed from the output of the WL Wiener filter using the inverse STFT. The effectiveness of the developed STFT-domain WL Wiener filter for binaural noise reduction is justified using experiments.

源语言英语
主期刊名25th European Signal Processing Conference, EUSIPCO 2017
出版商Institute of Electrical and Electronics Engineers Inc.
21-25
页数5
ISBN(电子版)9780992862671
DOI
出版状态已出版 - 23 10月 2017
活动25th European Signal Processing Conference, EUSIPCO 2017 - Kos, 希腊
期限: 28 8月 20172 9月 2017

出版系列

姓名25th European Signal Processing Conference, EUSIPCO 2017
2017-January

会议

会议25th European Signal Processing Conference, EUSIPCO 2017
国家/地区希腊
Kos
时期28/08/172/09/17

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