Abstract
We consider the problem of blind audio source separation. A method to solve this problem is blind source separation (BSS) using independent component analysis (ICA). ICA exploits the non-Gaussianity of source in the mixtures. In this paper we propose a new wavelet based ICA method using Kurtosis for blind audio source separation. In this method, the observations are transformed into an adequate representation using wavelet packets decomposition and Kurtosis criterion. We consider instantaneous mixture of four sources. The results of performance measures show a considerable improvement when compared to FastICA and similar method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.