diff MFCC.py @ 1:d5d4981b58f1

import MFCC code by Gyorgy Fazekas

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/MFCC.py	Wed Nov 14 13:15:15 2012 +0000
@@ -0,0 +1,108 @@
+'''MFCC.py
+
+Calculation of MFCC coefficients from frequency-domain data
+
+Adapted from the Vampy example plugin "PyMFCC" by Gyorgy Fazekas
+http://code.soundsoftware.ac.uk/projects/vampy/repository/entry/Example%20VamPy%20plugins/PyMFCC.py
+
+Centre for Digital Music, Queen Mary University of London.
+Copyright (C) 2009 Gyorgy Fazekas, QMUL.
+'''
+
+import sys,numpy
+from numpy import abs,log,exp,floor,sum,sqrt,cos,hstack
+from numpy.fft import *
+
+class melScaling(object):
+
+	def __init__(self,sampleRate,inputSize,numBands,minHz = 0,maxHz = None):
+		'''Initialise frequency warping and DCT matrix. 
+		Parameters:
+		sampleRate: audio sample rate
+		inputSize: length of magnitude spectrum (half of FFT size assumed)
+		numBands: number of mel Bands (MFCCs)
+		minHz: lower bound of warping  (default = DC)
+		maxHz: higher bound of warping (default = Nyquist frequency)
+		'''
+		self.sampleRate = sampleRate
+		self.NqHz = sampleRate / 2.0
+		self.minHz = minHz
+		if maxHz is None : maxHz = self.NqHz
+		self.maxHz = maxHz
+		self.inputSize = inputSize
+		self.numBands = numBands
+		self.valid = False
+		self.updated = False
+		
+	def update(self): 
+		# make sure this will run only once 
+		# if called from a vamp process
+		if self.updated: return self.valid
+		self.updated = True
+		self.valid = False
+		print 'Updating parameters and recalculating filters: '
+		print 'Nyquist: ',self.NqHz
+		
+		if self.maxHz > self.NqHz : 
+			raise Exception('Maximum frequency must be smaller than the Nyquist frequency')
+		
+		self.maxMel = 1000*log(1+self.maxHz/700.0)/log(1+1000.0/700.0)
+		self.minMel = 1000*log(1+self.minHz/700.0)/log(1+1000.0/700.0)
+		print 'minHz:%s\nmaxHz:%s\nminMel:%s\nmaxMel:%s\n' \
+		%(self.minHz,self.maxHz,self.minMel,self.maxMel)
+		self.filterMatrix = self.getFilterMatrix(self.inputSize,self.numBands)
+		self.DCTMatrix = self.getDCTMatrix(self.numBands)
+		self.filterIter = self.filterMatrix.__iter__()
+		self.valid = True
+		return self.valid
+				
+	def getFilterCentres(self,inputSize,numBands):
+		'''Calculate Mel filter centres around FFT bins.
+		This function calculates two extra bands at the edges for
+		finding the starting and end point of the first and last 
+		actual filters.'''
+		centresMel = numpy.array(xrange(numBands+2)) * (self.maxMel-self.minMel)/(numBands+1) + self.minMel
+		centresBin = numpy.floor(0.5 + 700.0*inputSize*(exp(centresMel*log(1+1000.0/700.0)/1000.0)-1)/self.NqHz)
+		return numpy.array(centresBin,int)
+		
+	def getFilterMatrix(self,inputSize,numBands):
+		'''Compose the Mel scaling matrix.'''
+		filterMatrix = numpy.zeros((numBands,inputSize))
+		self.filterCentres = self.getFilterCentres(inputSize,numBands)
+		for i in xrange(numBands) :
+			start,centre,end = self.filterCentres[i:i+3]
+			self.setFilter(filterMatrix[i],start,centre,end)
+		return filterMatrix.transpose()
+
+	def setFilter(self,filt,filterStart,filterCentre,filterEnd):
+		'''Calculate a single Mel filter.'''
+		k1 = numpy.float32(filterCentre-filterStart)
+		k2 = numpy.float32(filterEnd-filterCentre)
+		up = (numpy.array(xrange(filterStart,filterCentre))-filterStart)/k1
+		dn = (filterEnd-numpy.array(xrange(filterCentre,filterEnd)))/k2
+		filt[filterStart:filterCentre] = up
+		filt[filterCentre:filterEnd] = dn
+						
+	def warpSpectrum(self,magnitudeSpectrum):
+		'''Compute the Mel scaled spectrum.'''
+		return numpy.dot(magnitudeSpectrum,self.filterMatrix)
+		
+	def getDCTMatrix(self,size):
+		'''Calculate the square DCT transform matrix. Results are 
+		equivalent to Matlab dctmtx(n) with 64 bit precision.'''
+		DCTmx = numpy.array(xrange(size),numpy.float64).repeat(size).reshape(size,size)
+		DCTmxT = numpy.pi * (DCTmx.transpose()+0.5) / size
+		DCTmxT = (1.0/sqrt( size / 2.0)) * cos(DCTmx * DCTmxT)
+		DCTmxT[0] = DCTmxT[0] * (sqrt(2.0)/2.0)
+		return DCTmxT
+		
+	def dct(self,data_matrix):
+		'''Compute DCT of input matrix.'''
+		return numpy.dot(self.DCTMatrix,data_matrix)
+		
+	def getMFCCs(self,warpedSpectrum,cn=True):
+		'''Compute MFCC coefficients from Mel warped magnitude spectrum.'''
+		mfccs=self.dct(numpy.log(warpedSpectrum))
+		if cn is False : mfccs[0] = 0.0
+		return mfccs
+