CUED Publications database

Speech enhancement using an MMSE spectral amplitude estimator based on a modulation domain Kalman filter with a Gamma prior

Wang, Y and Brookes, M (2016) Speech enhancement using an MMSE spectral amplitude estimator based on a modulation domain Kalman filter with a Gamma prior. In: UNSPECIFIED pp. 5225-5229..

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Abstract

© 2016 IEEE. In this paper, we propose a minimum mean square error spectral estimator for clean speech spectral amplitudes that uses a Kalman filter to model the temporal dynamics of the spectral amplitudes in the modulation domain. Using a two-parameter Gamma distribution to model the prior distribution of the speech spectral amplitudes, we derive closed form expressions for the posterior mean and variance of the spectral amplitudes as well as for the associated update step of the Kalman filter. The performance of the proposed algorithm is evaluated on the TIMIT core test set using the perceptual evaluation of speech quality (PESQ) measure and segmental SNR measure and is shown to give a consistent improvement over a wide range of SNRs when compared to competitive algorithms.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Subjects: UNSPECIFIED
Divisions: Div F > Machine Intelligence
Depositing User: Cron Job
Date Deposited: 25 Jul 2017 03:57
Last Modified: 21 Nov 2017 03:06
DOI: