UCBSS

Introduction
This source code is the implementation of the underdetermined convolutive blind source separation algorithm proposed in [1].

Quick Start
At first add the “ucbss_dist” folder to MATLAB Path.
Please run “main.m”. It will load 2 channel mixed speech signals in the “data” directory, and then it separates the mixed signals to 3 original source signals. The result files will be saved in the “result” directory.

How to Cite
If you find it helpful, please cite [1]

Contact Information
For any questions and comments, please send your email to bluehawk2k@kaist.ac.kr

References
[1] Janghoon Cho and Chang D. Yoo. "Underdetermined Convolutive BSS: Bayes Risk Minimization Based on a Mixture of Super-Gaussian Posterior Approximation." Audio, Speech, and Language Processing, IEEE/ACM Transactions on 23.5 (2015): 828-839.

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License GPL v2
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Introduction

This source code is the implementation of the underdetermined convolutive blind source separation algorithm proposed in [1].

 

Quick Start

At first add the “ucbss_dist” folder to MATLAB Path.

Please run “main.m”. It will load 2 channel mixed speech signals in the “data” directory, and then it separates the mixed signals to 3 original source signals. The result files will be saved in the “result” directory.

 

How to Cite

If you find it helpful, please cite [1]

 

Contact Information

For any questions and comments, please send your email to bluehawk2k@kaist.ac.kr

 

References

[1] Janghoon Cho and Chang D. Yoo. "Underdetermined Convolutive BSS: Bayes Risk Minimization Based on a Mixture of Super-Gaussian Posterior Approximation." Audio, Speech, and Language Processing, IEEE/ACM Transactions on 23.5 (2015): 828-839.