Multi Band Spectral Subtraction for Speech Enhancement with Different Frequency Spacing Methods and their Effect on Objective Quality Measures
Author(s) -
P. Sunitha,
K. Satya Prasad
Publication year - 2019
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2019.05.06
Subject(s) - noise (video) , speech recognition , speech enhancement , computer science , cepstrum , quality (philosophy) , subtraction , mathematics , acoustics , background noise , artificial intelligence , physics , telecommunications , quantum mechanics , arithmetic , image (mathematics)
This paper mainly studies Multi Band Spectral Subtraction (MBSS) for speech enhancement based on the spectrum representation in the frequency domain with three different scales(linear, log, mel) and their effect on performance measures in presence of additive nonstationary noise at different ranges of input SNR. Since speech is non-stationary signal, noise distribution is nonuniform i.e few frequency components are affected severely than others. A common method to restore the original speech in presence of noise is speech enhancement by suppressing the back ground noise. Multi Band Spectral Subtraction is one among the speech enhancement techniques which performs spectral subtraction by dividing noisy speech spectrum into uniformly spaced non over lapping frequency bands and spectral over subtraction is performed in each band separately. The performance of this method is evaluated in terms of objective measures such as Cepstrum distance, Log Likelihood Ratio, Weighted Spectral Slope distance, segmental SNR and Perceptual Evaluation of Speech Quality.
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