NDLI: Perceptually-motivated selective suppression of late reverberation

Content Provider	IEEE Xplore Digital Library
Author	Tsilfidis, A. Mourjopoulos, J.
Copyright Year	2009
Description	Author affiliation: Audio and Acoustic Technology Group, WCL, Electrical Engineering and Computer Technology Department, University of Patras, 26500 Greece (Tsilfidis, A.; Mourjopoulos, J.)
Abstract	An improved spectral subtraction algorithm for suppressing late reverberation is presented. Existing spectral subtraction methods, process similarly all frames of the reverberant speech signal. This work introduces two criteria for the identification of the speech frames that do not contain significant late reverberation power. The subtraction is adequately relaxed in these frames in order to preserve the signal from unwanted distortions caused by overestimation errors. These novel relaxation criteria together with previous improvements on the conventional spectral subtraction algorithms (i.e. the introduction of a perceptually motivated non linear filtering technique) result in an improved estimation of the anechoic speech signal. Objective assessments in terms of Noise to Mask Ratio and Weighted Spectral Slope Distance are used to demonstrate the performance of the algorithm. The results indicate that the proposed method achieves sufficient late reverberation suppression with fewer transient and spectral distortions.
Starting Page	1
Ending Page	6
File Size	888668
Page Count	6
File Format	PDF
ISBN	9781424432974
DOI	10.1109/ICDSP.2009.5201165
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-05
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Reverberation Filtering Acoustic distortion Acoustic reflection Speech enhancement Degradation Masking threshold Robustness Speech processing Signal processing Auditory Masking Dereverberation Spectral Subtraction Speech Enhancement
Content Type	Text
Resource Type	Article

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