Distributed Multichannel Speech Enhancement with Minimum Mean-square Error Short-time Spectral Amplitude, Log-spectral Amplitude, and Spectral Phase Estimation

Document Type




Format of Original

12 p.

Publication Date




Source Publication

Signal Processing

Source ISSN


Original Item ID

doi: 10.1016/j.sigpro.2011.07.021


In this paper, the authors present optimal multichannel frequency domain estimators for minimum mean-square error (MMSE) short-time spectral amplitude (STSA), log-spectral amplitude (LSA), and spectral phase estimation in a widely distributed microphone configuration. The estimators utilize Rayleigh and Gaussian statistical models for the speech prior and noise likelihood with a diffuse noise field for the surrounding environment. Based on the Signal-to-Noise Ratio (SNR) and Segmental Signal-to-Noise Ratio (SSNR) along with the Log-Likelihood Ratio (LLR) and Perceptual Evaluation of Speech Quality (PESQ) as objective metrics, the multichannel LSA estimator decreases background noise and speech distortion and increases speech quality compared to the baseline single channel STSA and LSA estimators, where the optimal multichannel spectral phase estimator serves as a significant quantity to the improvements, and demonstrates robustness due to time alignment and attenuation factor estimation. Overall, the optimal distributed microphone spectral estimators show strong results in noisy environments with application to many consumer, industrial, and military products.


Signal Processing, Vol. 92, No. 2 (February 2012): 345-356. DOI.