Document Type
Article
Language
eng
Format of Original
12 p.
Publication Date
2-2012
Publisher
Elsevier
Source Publication
Signal Processing
Source ISSN
0165-1684
Original Item ID
doi: 10.1016/j.sigpro.2011.07.021
Abstract
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.
Recommended Citation
Trawicki, Marek B. and Johnson, Michael T., "Distributed Multichannel Speech Enhancement with Minimum Mean-square Error Short-time Spectral Amplitude, Log-spectral Amplitude, and Spectral Phase Estimation" (2012). Electrical and Computer Engineering Faculty Research and Publications. 56.
https://epublications.marquette.edu/electric_fac/56
ADA Accessible Version
Comments
Accepted version. Signal Processing, Vol. 92, No. 2 (February 2012): 345-356. DOI. © 2012 Elsevier. Used with permission.