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Description
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 |
This item appears in the following Collection(s)
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Dissertations and Theses - Electrical and Computer Engineering
Dissertations and Theses in Electrical and Computer Engineering -
Graduate Dissertations and Theses at Illinois
Graduate Theses and Dissertations at Illinois