NDLI: A Kalman filter based on wavelet filter-bank and psychoacoustic modeling for speech enhancement

Content Provider	IEEE Xplore Digital Library
Author	Yu Shao Chip-Hong Chang
Copyright Year	2006
Description	Author affiliation: Centre for High Performance Embedded Syst., Nanyang Technol. Univ., Singapore (Yu Shao; Chip-Hong Chang)
Abstract	This paper presents a subband adaptive filter based on wavelet filter-bank for speech enhancement. The adaptation of Kalman filter in wavelet domain has effectively reduced the non-stationary noise. A perceptual weighting filter exploiting the masking properties of psychoacoustic model is concatenated with the Kalman filter to further improve the intelligibility of speech. The proposed method owns its merits from the successful porting of Kalman filter into the wavelet domain so that speech analysis and enhancement can be carried out in time-frequency spectrum based on the human auditory model. Experimental results show that the speech enhancement system is capable of reducing noise with little speech degradation in adverse noise environments and the overall performance is superior to several competitive methods
Sponsorship	The Inst. of Electr. and Electron. Eng., Inc. Circuits and Syst. Soc. (IEEE CASS)
File Size	407059
File Format	PDF
ISBN	0780393899
DOI	10.1109/ISCAS.2006.1692537
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-05-21
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Psychology Psychoacoustic models Speech enhancement Noise reduction Adaptive filters Wavelet domain Working environment noise Concatenated codes Speech coding Wavelet analysis
Content Type	Text
Resource Type	Article

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