Masking-based beta-order MMSE speech enhancement
This paper considers an effective approach for attenuating acoustic noise and mitigating its effect in a speech signal. In this approach, human perceptual auditory masking effect is incorporated into an adaptive P-order minimum mean-square error (MMSE) speech enhancement algorithm. The relationship between the value of P and the noise-masking threshold is introduced and analyzed. The algorithm is based on a criterion by which the inaudible noise may be masked rather than suppressed. It thereby reduces the chance of distortion introduced to speech due to the enhancement process. In order to obtain an optimal estimation of the masking threshold, a modified way to measure the relative threshold offset is described. The performance of the proposed masking-based beta-order MMSE method has been evaluated through objective speech distortion measurement, spectrograin inspection and subjective listening tests. It is shown that the proposed method can achieve a more significant noise reduction and a better spectral estimation over the conventional adaptive beta-order MMSE method and the conventional over Subtraction noise-masking method. (c) 2005 Elsevier B.V. All rights reserved.
speech enhancement minimum mean-square error (mmse) masking properties