Noise reduction using multiple microphones remains a challenging and crucial research problem. This paper presents a new multichannel noise-reduction algorithm based on spatio-temporal prediction. Unlike many multichannel techniques that attempt to achieve both speech dereverberation and noise reduction at the same time, this new approach puts aside speech dereverberation and formulates the problem as one of estimating the speech component received at one microphone using the observations from all the available microphones. In comparison with the existing techniques such as beamforming, this new multichannel approach has many appealing properties: it does not require the knowledge of the source location or the channel impulse responses; the multiple microphones do not have to be arranged into a specific array geometry; it works the same for both the far-field and near-field cases; and most importantly, it can produce very good noise reduction with minimum speech distortion in real acoustic environments.
['Jacob Benesty', 'Jingdong Chen', 'Yiteng Huang']
A minimum speech distortion multichannel algorithm for noise reduction