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Dave Griffiths
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dave@fulmar.4739:1436183149
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/*
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* libmfcc.c - Code implementation for libMFCC
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* Copyright (c) 2010 Jeremy Sawruk
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*
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* This code is released under the MIT License.
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* For conditions of distribution and use, see the license in LICENSE
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*/
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#include <math.h>
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#include "libmfcc.h"
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/*
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* Computes the specified (mth) MFCC
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*
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* spectralData - array of doubles containing the results of FFT computation. This data is already assumed to be purely real
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* samplingRate - the rate that the original time-series data was sampled at (i.e 44100)
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* NumFilters - the number of filters to use in the computation. Recommended value = 48
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* binSize - the size of the spectralData array, usually a power of 2
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* m - The mth MFCC coefficient to compute
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*
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*/
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double GetCoefficient(double* spectralData, unsigned int samplingRate, unsigned int NumFilters, unsigned int binSize, unsigned int m)
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{
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double result = 0.0f;
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double outerSum = 0.0f;
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double innerSum = 0.0f;
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unsigned int k, l;
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// 0 <= m < L
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if(m >= NumFilters)
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{
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// This represents an error condition - the specified coefficient is greater than or equal to the number of filters. The behavior in this case is undefined.
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return 0.0f;
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}
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result = NormalizationFactor(NumFilters, m);
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for(l = 1; l <= NumFilters; l++)
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{
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// Compute inner sum
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innerSum = 0.0f;
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for(k = 0; k < binSize - 1; k++)
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{
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innerSum += fabs(spectralData[k] * GetFilterParameter(samplingRate, binSize, k, l));
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}
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if(innerSum > 0.0f)
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{
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innerSum = log(innerSum); // The log of 0 is undefined, so don't use it
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}
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innerSum = innerSum * cos(((m * PI) / NumFilters) * (l - 0.5f));
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outerSum += innerSum;
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}
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result *= outerSum;
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return result;
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}
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/*
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* Computes the Normalization Factor (Equation 6)
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* Used for internal computation only - not to be called directly
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*/
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double NormalizationFactor(int NumFilters, int m)
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{
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double normalizationFactor = 0.0f;
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if(m == 0)
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{
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normalizationFactor = sqrt(1.0f / NumFilters);
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}
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else
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{
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normalizationFactor = sqrt(2.0f / NumFilters);
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}
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return normalizationFactor;
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}
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/*
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* Compute the filter parameter for the specified frequency and filter bands (Eq. 2)
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* Used for internal computation only - not the be called directly
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*/
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double GetFilterParameter(unsigned int samplingRate, unsigned int binSize, unsigned int frequencyBand, unsigned int filterBand)
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{
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double filterParameter = 0.0f;
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double boundary = (frequencyBand * samplingRate) / binSize; // k * Fs / N
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double prevCenterFrequency = GetCenterFrequency(filterBand - 1); // fc(l - 1) etc.
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double thisCenterFrequency = GetCenterFrequency(filterBand);
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double nextCenterFrequency = GetCenterFrequency(filterBand + 1);
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if(boundary >= 0 && boundary < prevCenterFrequency)
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{
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filterParameter = 0.0f;
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}
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else if(boundary >= prevCenterFrequency && boundary < thisCenterFrequency)
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{
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filterParameter = (boundary - prevCenterFrequency) / (thisCenterFrequency - prevCenterFrequency);
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filterParameter *= GetMagnitudeFactor(filterBand);
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}
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else if(boundary >= thisCenterFrequency && boundary < nextCenterFrequency)
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{
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filterParameter = (boundary - nextCenterFrequency) / (thisCenterFrequency - nextCenterFrequency);
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filterParameter *= GetMagnitudeFactor(filterBand);
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}
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else if(boundary >= nextCenterFrequency && boundary < samplingRate)
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{
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filterParameter = 0.0f;
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}
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return filterParameter;
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}
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/*
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* Compute the band-dependent magnitude factor for the given filter band (Eq. 3)
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* Used for internal computation only - not the be called directly
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*/
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double GetMagnitudeFactor(unsigned int filterBand)
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{
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double magnitudeFactor = 0.0f;
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if(filterBand >= 1 && filterBand <= 14)
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{
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magnitudeFactor = 0.015;
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}
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else if(filterBand >= 15 && filterBand <= 48)
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{
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magnitudeFactor = 2.0f / (GetCenterFrequency(filterBand + 1) - GetCenterFrequency(filterBand -1));
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}
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return magnitudeFactor;
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}
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/*
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* Compute the center frequency (fc) of the specified filter band (l) (Eq. 4)
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* This where the mel-frequency scaling occurs. Filters are specified so that their
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* center frequencies are equally spaced on the mel scale
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* Used for internal computation only - not the be called directly
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*/
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double GetCenterFrequency(unsigned int filterBand)
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{
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double centerFrequency = 0.0f;
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double exponent;
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if(filterBand == 0)
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{
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centerFrequency = 0;
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}
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else if(filterBand >= 1 && filterBand <= 14)
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{
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centerFrequency = (200.0f * filterBand) / 3.0f;
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}
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else
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{
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exponent = filterBand - 14.0f;
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centerFrequency = pow(1.0711703, exponent);
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centerFrequency *= 1073.4;
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}
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return centerFrequency;
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}
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@ -1,26 +0,0 @@
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/*
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* libmfcc.h - Header for libMFCC
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* Copyright (c) 2010 Jeremy Sawruk
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*
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* This code is released under the MIT License.
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* For conditions of distribution and use, see the license in LICENSE
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*/
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#pragma once
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#define PI 3.14159265358979323846264338327
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// Returns the specified (mth) MFCC
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double GetCoefficient(double* spectralData, unsigned int samplingRate, unsigned int NumFilters, unsigned int binSize, unsigned int m);
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// Compute the normalization factor (For internal computation only - not to be called directly)
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double NormalizationFactor(int NumFilters, int m);
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// Compute the filter parameter for the specified frequency and filter bands (For internal computation only - not the be called directly)
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double GetFilterParameter(unsigned int samplingRate, unsigned int binSize, unsigned int frequencyBand, unsigned int filterBand);
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// Compute the band-dependent magnitude factor for the given filter band (For internal computation only - not the be called directly)
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double GetMagnitudeFactor(unsigned int filterBand);
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// Compute the center frequency (fc) of the specified filter band (l) (For internal computation only - not the be called directly)
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double GetCenterFrequency(unsigned int filterBand);
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@ -1,35 +0,0 @@
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#include "sample.h"
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#include <vector>
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class brain_block {
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// runs analysis on pcm
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brain_block(const sample &pcm);
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// returns distance based on ratio of fft-mfcc values
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float compare(const brain_block &other, float ratio);
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public:
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sample m_pcm;
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sample m_fft;
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sample m_mfcc;
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};
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class sample_brain {
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public:
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sample_brain();
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// rewrites whole brain
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void init(u32 block_size, u32 overlap);
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// take another brain and rebuild this brain from bits of that one
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// (presumably this one is made from a single sample)
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sample resynth(const sample_brain *other, ratio);
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private:
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vector<brain_block> m_brain;
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u32 m_block_size;
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u32 m_overlap;
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};
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