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Title:Online parameter selection for source separation using non-negative matrix factorization
Author(s):Kang, Kang
Advisor(s):Smaragdis, Paris
Department / Program:Electrical & Computer Eng
Discipline:Electrical & Computer Engr
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Non-negative matrix factorization
source separation
spectral subtraction
noise removal
speech enhancement
Abstract:Blind source separation has been an area of study recently due to the many applications that might benefit from a good blind source separation algo- rithm. One instance is using blind source separation for audio denoising in cellular phones. In almost all instances, we have very little, if any, infor- mation about how background noise is mixed with the speaker’s voice in a given cell phone conversation. Current techniques include spectral subtrac- tion and Wiener filtering which are classical DSP techniques to deal with stationary noises. In this document, we aim to present a study on how to use blind source separation algorithms to denoise audio mixtures containing speech and various background noises. We mainly focus on how to imple- ment an online source separation algorithm which can handle non-stationary noises. To address the implementation, we also present a study on how to select the parameters in the separation algorithm in order to deliver the best performance for denoising using a statistical metric we have defined.
Issue Date:2012-09-18
URI:http://hdl.handle.net/2142/34281
Rights Information:Copyright 2012 Kang Kang
Date Available in IDEALS:2012-09-18
Date Deposited:2012-08


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