Time series: data analysis and theory
Time series: data analysis and theory
EURASIP Journal on Applied Signal Processing
IEICE - Transactions on Information and Systems
Nonlinear speech enhancement: an overview
Progress in nonlinear speech processing
Multichannel Cepstral Domain Feature Warping for Robust Speech Recognition
Proceedings of the 2011 conference on Neural Nets WIRN10: Proceedings of the 20th Italian Workshop on Neural Nets
A matlab implementation of an algorithm for computing integrals of products of bessel functions
ICMS'06 Proceedings of the Second international conference on Mathematical Software
Compressive speech enhancement
Speech Communication
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This paper introduces two short-time spectral amplitude estimators for speech enhancement with multiple microphones. Based on joint Gaussian models of speech and noise Fourier coefficients, the clean speech amplitudes are estimated with respect to the MMSE or the MAP criterion. The estimators outperform single microphone minimum mean square amplitude estimators when the speech components are highly correlated and the noise components are sufficiently uncorrelated. Whereas the first MMSE estimator also requires knowledge of the direction of arrival, the second MAP estimator performs a direction-independent noise reduction. The estimators are generalizations of the well-known single channel MMSE estimator derived by Ephraim and Malah (1984) and the MAP estimator derived by Wolfe and Godsill (2001), respectively.