The diarization stuff inside the (Diarization) VM which can now be found at http://github.com/srvk/DiViMe

New usage supports multiple files

• Start with a folder full of .wav files to be processed
• Path to the root folder (here! OpenSat/)
• give the command ./runDiarNoisemes.sh <folder holding .wav files>

The system will grind first creating features for all the .wav files it found, then will place those features in a subfolder feature. Then it will load a model, and process all the features generated, producing output in a subfolder hyp as two files (for now): confidence.mat and confidence.pkl.gz - a confidence matrix in Matlab v5 mat-file format, and a Python compressed data 'pickle' file

More details are in the DiairzationVM README