Acoustical Society of America | Liu F, Demosthenous A, Yasin I | Signal-to-noise ratio (SNR) estimation is necessary for many speech processing applications often challenged by nonstationary noise....
Auditory filter-bank compression improves estimation of signal-to-noise-ratio for speech in noise
Abstract
Signal-to-noise ratio (SNR) estimation is necessary for many speech processing applications often challenged by nonstationary noise. The authors have previously demonstrated that the variance of spectral entropy (VSE) is a reliable estimate of SNR in nonstationary noise. Based on pre-estimated VSE-SNR relationship functions, the SNR of unseen acoustic environments can be estimated from the measured VSE. This study predicts that introducing a compressive function based on cochlear processing will increase the stability of the pre-estimated VSE-SNR relationship functions. This study demonstrates that calculating the VSE based on a nonlinear filter-bank, simulating cochlear compression, reduces the VSE-based SNR estimation errors. VSE-SNR relationship functions were estimated using speech tokens presented in babble noise comprised of different numbers of speakers. Results showed that the coefficient of determination (R2) of the estimated VSE-SNR relationship functions have absolute percentage improvements of over 26% when using a filter-bank with a compressive function, compared to when using a linear filter-bank without compression. In 2-talker babble noise, the estimation accuracy is more than 3 dB better than other published methods.
Publication Type: | Journal Article |
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Publication Sub Type | Article |
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Authors: | Liu F, Demosthenous A, Yasin I |
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Publisher: | Acoustical Society of America |
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Publication date: | 05/05/2020 |
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Journal | Journal of the Acoustical Society of America |
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Volume: | 147 |
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Issue: | 5 |
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Status | Published |
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Print ISSN | 0001-4966 |
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DOI: | |
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Full Text URL: | |
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