def getSignalFromMelGram( self, melGram, hop=64 ):
hopScale = 4
randomSignal = 2*np.random.rand( melGram.shape[0]*hop + hop*hopScale ) - 1
randomSpectrogram = utility.getSpectrogram( randomSignal, hop=hop, frameSize=hop*hopScale )
#randomSpectrogram = np.random.randn( melGram.shape[0], hop*hopScale/2 + 1 ) + np.random.randn( melGram.shape[0], hop*hopScale/2 + 1 )*1j
#randomSpectrogram[:, 0] = randomSpectrogram[:, 0].real + 0j
#randomSpectrogram[:, -1] = randomSpectrogram[:, -1].real + 0j
spectrogramScaler = np.zeros( randomSpectrogram.shape )
filters = self.MFCCer.getFilters( hop*hopScale, self.fs, 0, None, 0 )
for n in xrange( randomSpectrogram.shape[0] ):
spectrogramScaler[n] = np.sum( filters*melGram[n], axis=1 )
#spectrogramScaler[n] = np.sum( filters, axis=1 )
return utility.getSignalFromSpectrogram( randomSpectrogram*spectrogramScaler, hop, np.hanning( hop*hopScale ) )
import separateHarmonicPercussive
import sys
import os
import melNoiseTransform
if __name__ == "__main__":
if len(sys.argv) < 2:
print "Usage: %s audio.wav" % (sys.argv[0])
sys.exit()
audioData, fs = utility.getAudioData( sys.argv[1] )
hop = 1024
frameSize = 4096
spectrogram = utility.getSpectrogram( audioData, hop=hop, frameSize=frameSize )
seperator = separateHarmonicPercussive.HarmonicPercussiveSeparator( spectrogram )
harmonicSignal = utility.getSignalFromSpectrogram( seperator.harmonicSpectrogram, hop, np.hanning( frameSize ) )
percussiveSignal = utility.getSignalFromSpectrogram( seperator.percussiveSpectrogram, hop, np.hanning( frameSize ) )
impulse = np.zeros( 10000 )
impulse[0] = 1.0
kernelDictionary = ERBFilters.ERBFiltersToKernels( impulse, ERBFilters.makeERBFilters( fs, 200, 100, 5000 ) )
reconstructedHarmonicSignal, residual, scales, kernels, offsets = spikeGramTest.matchingPursuit( kernelDictionary, harmonicSignal, 16, 0, (2000.0*audioData.shape[0])/fs )
melTransformer = melNoiseTransform.melTransformer( fs )
N = np.min( [percussiveSignal.shape[0], residual.shape[0]] )
reconstructedNoiseSignal = melTransformer.getSignalFromMelGram( melTransformer.getMelGram( percussiveSignal[:N] + residual[:N] ) )
reconstructedNoiseSignal /= np.max( np.abs( reconstructedNoiseSignal ) )
reconstructedHarmonicSignal /= np.max( np.abs( reconstructedHarmonicSignal ) )
N = np.min( [reconstructedHarmonicSignal.shape[0], reconstructedNoiseSignal.shape[0]] )