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