DocumentCode
3510812
Title
Subband nonstationary noise reduction based on multichannel spatial prediction under reverberant environments
Author
Togami, Masahito ; Kawaguchi, Yohei ; Obuchi, Yasunari
Author_Institution
Central Res. Lab., Hitachi Ltd., Kokubunji
fYear
2009
fDate
19-24 April 2009
Firstpage
133
Lastpage
136
Abstract
We propose a novel non-stationary and convolutive noise reduction method under reverberant environments. Unlike many multichannel noise reduction methods, the proposed method does not need pre knowledge of impulse response or direction of arrival (DOA) of the target source. The proposed method is composed of two processes. On the noise reduction process, the noise component is reduced without the impulse response of the target source. The target source component in the output signal is distorted, but the distortion is removed by the distortion-restoration process. Importantly, possibility of complete noise reduction with no distortion based on the proposed framework is assured by MINT theory. Experimental results under the reverberant environment (RT60 ap 300 ms) show that the proposed method can reduce more noise than the conventional method and the distortion of the target source is not so big.
Keywords
acoustic signal processing; reverberation; signal denoising; transient response; direction of arrival estimation; distortion-restoration process; impulse response; multichannel spatial prediction; subband nonstationary noise reduction; target source component; Acoustic noise; Distortion; Microphone arrays; Noise cancellation; Noise reduction; Reverberation; Signal processing; Video recording; Videoconference; Working environment noise; multichannel noise reduction; reverberation; spatial prediction; subband;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location
Taipei
ISSN
1520-6149
Print_ISBN
978-1-4244-2353-8
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2009.4959538
Filename
4959538
Link To Document