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

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Electrical & Computer Engr

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2012

Author dc:creator

• Kang, Kang

Contributors dc:contributor

• Smaragdis, Paris

• Non-negative matrix factorization
• source separation
• spectral subtraction
• noise removal
• speech enhancement

Statement dc:rights

• Copyright 2012 Kang Kang

Language dc:language

en

Handle dc:identifier

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

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/34281