DocumentCode :
2372077
Title :
Theoretical analysis of iterative weak spectral subtraction via higher-order statistics
Author :
Inoue, Takayuki ; Saruwatari, Hiroshi ; Takahashi, Yu. ; Shikano, Kiyorhiro ; Kondo, Kazunobu
Author_Institution :
Nara Inst. of Sci. & Technol., Nara, Japan
fYear :
2010
fDate :
Aug. 29 2010-Sept. 1 2010
Firstpage :
220
Lastpage :
225
Abstract :
In this paper, we provide a new theoretical analysis of the amount of musical noise generated via iterative spectral subtraction based on higher-order statistics. To achieve high-quality noise reduction with low musical noise, the iterative spectral subtraction method, i.e., recursively applied weak nonlinear signal processing, has been proposed. Although the effectiveness of the method has been reported experimentally, there have been no theoretical studies. Therefore, in this paper, we formulate the generation process of musical noise by tracing the change in kurtosis, and conduct a comparison of the amount of musical noise for different parameter settings under the same noise reduction performance. It is clarified from mathematical analysis and evaluation experiments that iterative spectral subtraction with very weak processing can result in the generation of less musical noise.
Keywords :
interference suppression; iterative methods; spectral analysis; speech processing; higher-order statistics; iterative weak spectral subtraction; kurtosis; musical noise; weak nonlinear signal processing; Iterative methods; Noise; Noise measurement; Noise reduction; Shape; Speech;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on
Conference_Location :
Kittila
ISSN :
1551-2541
Print_ISBN :
978-1-4244-7875-0
Electronic_ISBN :
1551-2541
Type :
conf
DOI :
10.1109/MLSP.2010.5589167
Filename :
5589167
Link To Document :
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