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A GENERALIZED LOG-SPECTRAL AMPLITUDE ESTIMATOR FOR SINGLE-CHANNEL SPEECH ENHANCEMENT

Citation Author(s):
Aleksej Chinaev and Reinhold Haeb-Umbach
Submitted by:
Aleksej Chinaev
Last updated:
3 September 2021 - 10:39am
Document Type:
Presentation Slides
Document Year:
2017
Event:
Presenters Name:
Aleksej Chinaev
Paper Code:
SP-L6

Abstract 

Abstract: 

The benefits of both a logarithmic spectral amplitude (LSA) estimation and a modeling in a generalized spectral domain (where short-time amplitudes are raised to a generalized power exponent, not restricted to magnitude or power spectrum) are combined in this contribution to achieve a better tradeoff between speech quality and noise suppression in single-channel speech enhancement. A novel gain function is derived to enhance the logarithmic generalized spectral amplitudes of noisy speech. Experiments on the CHiME-3 dataset show that it outperforms the famous minimum mean squared error (MMSE) LSA gain function of Ephraim and Malah in terms of noise suppression by 1.4 dB, while the good speech quality of the MMSE-LSA estimator is maintained.

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Dataset Files

ICASSP_2017_PaperID_2020_slides.pdf

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