I am really impressed with the match add-on to Sonic Visualizer as it took samples from two speakers at difference cadence and pitch and matched them perfectly!! I should be able to match stars "voices" with this pretty easily.
I discovered Sonic Visualizer, which seems useful for sound analysis. I have also tested loris some more and it doesn't like files that are stereo or with any extraneous header info, but seems to work quite well. I am considering a merger of opencv and frequency spectrum plots to see if opencv can identify the face of a star by its spectrum. I would assume that if the same framework was maintained, it would work. I am also testing to see if I can generate a spectrogram of words by various speakers and see if they can be found to match with opencv.
import loris filea="AiffSample" #Load the input file fin = loris.AiffFile( filea+".aiff" ) samples = fin.samples() sr = fin.sampleRate() #Configure the analyzer component FUNDAMENTAL = 415.0 myAnalyzer = loris.Analyzer( .8 * FUNDAMENTAL, FUNDAMENTAL ); myAnalyzer.setFreqDrift( .2 * FUNDAMENTAL ); # analyze and store partials partials = myAnalyzer.analyze( samples, sr ); print 'found %d partials'%( partials.size() ) # export and save to SDIF file fsdif = loris.SdifFile( partials ) fsdif.write( filea+".sdif" ) # synthesize sampsout = loris.synthesize( partials, sr ) # export samples to AIFF file faiff = loris.AiffFile( sampsout, sr ) faiff.write( filea+"2.aiff" ) exit()