MMSE BASED NOISE PSD TRACKING WITH LOW COMPLEXITY

TitleMMSE BASED NOISE PSD TRACKING WITH LOW COMPLEXITY
Publication TypeConference Proceedings
Year of Publication2010
AuthorsHendriks, RC, Heusdens, R, Jensen, J
Refereed DesignationRefereed
Conference NameIEEE International Conference on Acoustics, Speech and Signal Processing
Pagination4266-4269
Date Published03/2010
Conference LocationDallas, TX
ISBN Number978-1-4244-4296-6
KeywordsNoise PSD estimation, speech enhancement
Abstract

Most speech enhancement algorithms heavily depend on the noise power spectral density (PSD). Because this quantity is unknown in practice, estimation from the noisy data is necessary. We present a low complexity method for noise PSD estimation. The algorithm is based on a minimum mean-squared error estimator of the noise magnitude-squared DFT coefficients. Compared to minimum statistics based noise tracking, segmental SNR and PESQ are improved for non-stationary noise sources with 1 dB and 0.25 MOS points, respectively. Compared to recently published algorithms, similar good noise tracking performance is obtained, but at a computational complexity that is in the order of a factor 40 lower.

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