Document Type
Conference Proceeding
Language
eng
Format of Original
4 p.
Publication Date
4-6-2015
Publisher
Institute of Electrical and Electronics Engineers
Source Publication
IEEE International Conference on Acoustics, Speech and Signal Processing, 2003
Source ISSN
1520-6149
Original Item ID
doi: 10.1109/ICASSP.2003.1198932
Abstract
The paper presents the implementation of two nonlinear noise reduction methods applied to speech enhancement. The methods are based on embedding the noisy signal in a high-dimensional reconstructed phase space and applying singular value decomposition to project the signal into a lower dimension. The advantages of these nonlinear methods include that they do not require explicit models of noise spectra and do not have the typical "musical tone" side effects associated with traditional linear speech enhancement methods. The proposed nonlinear methods are compared with traditional speech enhancement techniques, including spectral subtraction, Wiener filtering, and Ephraim-Malah filtering, on example speech utterances with additive white noise for a variety of SNR levels. The results show that the local nonlinear noise reduction method outperforms Wiener filtering and spectral subtraction, but not Ephraim-Malah filtering, as had been suggested by previous studies.
Recommended Citation
Johnson, Michael T.; Lindgren, Andrew C.; Povinelli, Richard J.; and Yuan, Xiaolong, "Performance of Nonlinear Speech Enhancement using Phase Space Reconstruction" (2015). Electrical and Computer Engineering Faculty Research and Publications. 123.
https://epublications.marquette.edu/electric_fac/123
Comments
Accepted version. Published as part of the proceedings of the conference, IEEE International Conference on Acoustics, Speech and Signal Processing, 2003: 920-923 (Vol. 1). DOI. © 2003 Institute of Electrical and Electronic Engineers (IEEE). Used with permission.