Speech enhancement techniques using spectral subtraction have the drawback of generating an annoying musical noise. We develop a new post-processing method for reducing it in each critical-band. In the proposed technique, the difference between tonality coefficients of the noisy speech and the denoised one constitutes one step for detection. Next, using a modified Johnston masking threshold, we detect the so-called "critical-band musical noise". The reduction is simply done by undertaking the power spectral density of detected musical noise under the masking thresholds. Simulation results using different criteria are presented to validate proposed ideas and to show that enhanced speech is characterized by low distortion and inaudible musical noise.
|bruite_10.wav||bruite_10.wav Sentence extracted from the data base TIMIT (She had your dark suit in greasy wash water all year) and corrupted by an additive white Gaussian noise at SNR=10 dB|
|wiener_10.wav||Denoised signal using Wiener technique|
|previous_10.wav||Enhanced signal using previous developed perceptual technique based on identifying musical noise|
|our_10.wav||Enhanced signal using the proposed approach based on musical noise reduction using critical bands tonality coefficients and masking thresholds|
Bibliographic reference. Aicha, Anis Ben / Jebara, Sofia Ben (2007): "Perceptual musical noise reduction using critical bands tonality coefficients and masking thresholds", In INTERSPEECH-2007, 822-825.