On the use of contextual time frequency information for full-band clustering-based convolutive blind source separation - Atcheson, M.; Jafari, I.; Togneri, R.; Nordholm, Sven (IEEE, 2014)
In this paper we propose to incorporate contextual time frequency information for clustering-based blind source separation. Previous clustering-based approaches have successfully used clustering techniques to estimate time-frequency separation masks; however, these approaches generally do not consider the contextual information of each time-frequency slot. Motivated by the homogenous behavior of speech signals, we modify the fuzzy c-means clustering to bias the results in favor of cluster membership homogeneity within localized neighborhoods in the time-frequency space. Experimental evaluations in both simulated and real-world underdetermined environments demonstrate improvement in source separation performance over previous clustering approaches.