@inproceedings{f231f7fafa7141bcb7e0186ddb61638b,
title = "On the Design and Implementation of Maximum SNR Beamformers for Scattered Speech Sources",
abstract = "Most existing microphone array beamforming methods for speech signal extraction assume that speech sources obey the point source model. However, this assumption is not applicable in many practical scenarios where small-spacing and small-size microphone arrays are employed, thereby rendering the size of the sources non-negligible. To deal with this situation, the scattered source model should be used, which is investigated in this work. With this model, we derive two versions of the maximum signal-to-noise ratio (SNR) beamformer: one maximizes the SNR with minimum mean-squared error (MSE) and the other maximizes the SNR with minimum speech distortion. We show that the one with minimum MSE can be decomposed as the product between the one with minimum speech distortion and a single-channel Wiener postfilter. We then propose a multichannel approach to estimating the postfilter through noise field modeling. The performance evaluation of the developed beamformers and postfilter is conducted via simulations.",
keywords = "Maximum SNR beamforming, postfiltering, scattered sources, speech enhancement",
author = "Fan Zhang and Chao Pan and Jacob Benesty and Jingdong Chen",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023 ; Conference date: 14-11-2023 Through 17-11-2023",
year = "2023",
doi = "10.1109/ICSPCC59353.2023.10400316",
language = "英语",
series = "Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of 2023 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2023",
}