Source number estimation in reverberant conditions via full-band weighted, adaptive fuzzy c-means clustering
Joshua Hollick, Ingrid Jafari, Roberto B. Togneri, Sven Erik Nordholm · 2014
We introduce a novel approach for source number estimation through an adaptive fuzzy c-means clustering. Spatial feature vectors are extracted from microphone observations, weighted for reliability and then clustered in a full-band manner using an adaptive variation on the fuzzy c-means. A number of quality measures are combined to produce a weighted sum which is used to find the optimal number of clusters at each iteration of the clustering algorithm. Experimental evaluations using real-world recordings from a reverberant room (RT60= 390 ms) demonstrated encouraging performance in both even- and under-determined conditions.