8th European Conference on Speech Communication and Technology

Geneva, Switzerland
September 1-4, 2003


Perceptually-Constrained Generalized Singular Value Decomposition-Based Approach for Enhancing Speech Corrupted by Colored Noise

Gwo-hwa Ju, Lin-shan Lee

National Taiwan University, Taiwan

In a previous work, we have successfully integrated the transformation-based signal subspace technique with the generalized singular value decomposition (GSVD) algorithm to develop an improved speech enhancement framework [1]. In this paper, we further incorporate the perceptual masking effect of the psychoacoustics model as extra constraints of the previously proposed GSVD-based algorithm to obtain improved sound feature, and furthermore make sure the undesired residual noise to be nearly unperceivable. Both subjective listening tests and spectrogram-plot comparison showed that the closed-form solution developed here can offer significantly better speech quality than either the conventional spectral subtraction algorithm or the previously proposed GSVD-based technique, regardless of whether the additive noise is white or not.

Full Paper

Bibliographic reference.  Ju, Gwo-hwa / Lee, Lin-shan (2003): "Perceptually-constrained generalized singular value decomposition-based approach for enhancing speech corrupted by colored noise", In EUROSPEECH-2003, 533-536.