A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Unsupervised Learning based Modified C- ICA for Audio Source Separation in Blind Scenario
2016
International Journal of Information Technology and Computer Science
Separating audio sources from a convolutive mixture of signals from various independent sources is a very fascinating area in personal and professional context. The task of source separation becomes trickier when there is no idea about mixing environment and can be termed as blind audio source separation (BASS). Mixing scenario becomes more complicated when there is a difference between number of audio sources and number of recording microphones, under determined and over determined mixing. The
doi:10.5815/ijitcs.2016.03.02
fatcat:346wb4p2ebb6poyyipi5g4xgiu