Online parameter selection for source separation using non-negative matrix factorization

Kang, Kang

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https://hdl.handle.net/2142/34281 Copy

Description

Title

Online parameter selection for source separation using non-negative matrix factorization

Author(s)

Kang, Kang

Issue Date

2012-09-18T21:09:22Z

Director of Research (if dissertation) or Advisor (if thesis)

Smaragdis, Paris

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(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.

Graduation Semester

2012-08

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http://hdl.handle.net/2142/34281

Copyright and License Information

Copyright 2012 Kang Kang

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