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livetrax/libs/qm-dsp/dsp/segmentation/ClusterMeltSegmenter.cpp
Paul Davis 3deba1921b add queen mary DSP library
git-svn-id: svn://localhost/ardour2/branches/3.0@9029 d708f5d6-7413-0410-9779-e7cbd77b26cf
2011-03-02 12:37:39 +00:00

399 lines
11 KiB
C++

/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
/*
* ClusterMeltSegmenter.cpp
*
* Created by Mark Levy on 23/03/2006.
* Copyright 2006 Centre for Digital Music, Queen Mary, University of London.
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License as
published by the Free Software Foundation; either version 2 of the
License, or (at your option) any later version. See the file
COPYING included with this distribution for more information.
*/
#include <cfloat>
#include <cmath>
#include "ClusterMeltSegmenter.h"
#include "cluster_segmenter.h"
#include "segment.h"
#include "dsp/transforms/FFT.h"
#include "dsp/chromagram/ConstantQ.h"
#include "dsp/rateconversion/Decimator.h"
#include "dsp/mfcc/MFCC.h"
ClusterMeltSegmenter::ClusterMeltSegmenter(ClusterMeltSegmenterParams params) :
window(NULL),
fft(NULL),
constq(NULL),
mfcc(NULL),
featureType(params.featureType),
hopSize(params.hopSize),
windowSize(params.windowSize),
fmin(params.fmin),
fmax(params.fmax),
nbins(params.nbins),
ncomponents(params.ncomponents), // NB currently not passed - no. of PCA components is set in cluser_segmenter.c
nHMMStates(params.nHMMStates),
nclusters(params.nclusters),
histogramLength(params.histogramLength),
neighbourhoodLimit(params.neighbourhoodLimit),
decimator(NULL)
{
}
void ClusterMeltSegmenter::initialise(int fs)
{
samplerate = fs;
if (featureType == FEATURE_TYPE_CONSTQ ||
featureType == FEATURE_TYPE_CHROMA) {
// run internal processing at 11025 or thereabouts
int internalRate = 11025;
int decimationFactor = samplerate / internalRate;
if (decimationFactor < 1) decimationFactor = 1;
// must be a power of two
while (decimationFactor & (decimationFactor - 1)) ++decimationFactor;
if (decimationFactor > Decimator::getHighestSupportedFactor()) {
decimationFactor = Decimator::getHighestSupportedFactor();
}
if (decimationFactor > 1) {
decimator = new Decimator(getWindowsize(), decimationFactor);
}
CQConfig config;
config.FS = samplerate / decimationFactor;
config.min = fmin;
config.max = fmax;
config.BPO = nbins;
config.CQThresh = 0.0054;
constq = new ConstantQ(config);
constq->sparsekernel();
ncoeff = constq->getK();
fft = new FFTReal(constq->getfftlength());
} else if (featureType == FEATURE_TYPE_MFCC) {
// run internal processing at 22050 or thereabouts
int internalRate = 22050;
int decimationFactor = samplerate / internalRate;
if (decimationFactor < 1) decimationFactor = 1;
// must be a power of two
while (decimationFactor & (decimationFactor - 1)) ++decimationFactor;
if (decimationFactor > Decimator::getHighestSupportedFactor()) {
decimationFactor = Decimator::getHighestSupportedFactor();
}
if (decimationFactor > 1) {
decimator = new Decimator(getWindowsize(), decimationFactor);
}
MFCCConfig config(samplerate / decimationFactor);
config.fftsize = 2048;
config.nceps = 19;
config.want_c0 = true;
mfcc = new MFCC(config);
ncoeff = config.nceps + 1;
}
}
ClusterMeltSegmenter::~ClusterMeltSegmenter()
{
delete window;
delete constq;
delete decimator;
delete fft;
}
int
ClusterMeltSegmenter::getWindowsize()
{
return static_cast<int>(windowSize * samplerate + 0.001);
}
int
ClusterMeltSegmenter::getHopsize()
{
return static_cast<int>(hopSize * samplerate + 0.001);
}
void ClusterMeltSegmenter::extractFeatures(const double* samples, int nsamples)
{
if (featureType == FEATURE_TYPE_CONSTQ ||
featureType == FEATURE_TYPE_CHROMA) {
extractFeaturesConstQ(samples, nsamples);
} else if (featureType == FEATURE_TYPE_MFCC) {
extractFeaturesMFCC(samples, nsamples);
}
}
void ClusterMeltSegmenter::extractFeaturesConstQ(const double* samples, int nsamples)
{
if (!constq) {
std::cerr << "ERROR: ClusterMeltSegmenter::extractFeaturesConstQ: "
<< "No const-q: initialise not called?"
<< std::endl;
return;
}
if (nsamples < getWindowsize()) {
std::cerr << "ERROR: ClusterMeltSegmenter::extractFeatures: nsamples < windowsize (" << nsamples << " < " << getWindowsize() << ")" << std::endl;
return;
}
int fftsize = constq->getfftlength();
if (!window || window->getSize() != fftsize) {
delete window;
window = new Window<double>(HammingWindow, fftsize);
}
vector<double> cq(ncoeff);
for (int i = 0; i < ncoeff; ++i) cq[i] = 0.0;
const double *psource = samples;
int pcount = nsamples;
if (decimator) {
pcount = nsamples / decimator->getFactor();
double *decout = new double[pcount];
decimator->process(samples, decout);
psource = decout;
}
int origin = 0;
// std::cerr << "nsamples = " << nsamples << ", pcount = " << pcount << std::endl;
int frames = 0;
double *frame = new double[fftsize];
double *real = new double[fftsize];
double *imag = new double[fftsize];
double *cqre = new double[ncoeff];
double *cqim = new double[ncoeff];
while (origin <= pcount) {
// always need at least one fft window per block, but after
// that we want to avoid having any incomplete ones
if (origin > 0 && origin + fftsize >= pcount) break;
for (int i = 0; i < fftsize; ++i) {
if (origin + i < pcount) {
frame[i] = psource[origin + i];
} else {
frame[i] = 0.0;
}
}
for (int i = 0; i < fftsize/2; ++i) {
double value = frame[i];
frame[i] = frame[i + fftsize/2];
frame[i + fftsize/2] = value;
}
window->cut(frame);
fft->process(false, frame, real, imag);
constq->process(real, imag, cqre, cqim);
for (int i = 0; i < ncoeff; ++i) {
cq[i] += sqrt(cqre[i] * cqre[i] + cqim[i] * cqim[i]);
}
++frames;
origin += fftsize/2;
}
delete [] cqre;
delete [] cqim;
delete [] real;
delete [] imag;
delete [] frame;
for (int i = 0; i < ncoeff; ++i) {
cq[i] /= frames;
}
if (decimator) delete[] psource;
features.push_back(cq);
}
void ClusterMeltSegmenter::extractFeaturesMFCC(const double* samples, int nsamples)
{
if (!mfcc) {
std::cerr << "ERROR: ClusterMeltSegmenter::extractFeaturesMFCC: "
<< "No mfcc: initialise not called?"
<< std::endl;
return;
}
if (nsamples < getWindowsize()) {
std::cerr << "ERROR: ClusterMeltSegmenter::extractFeatures: nsamples < windowsize (" << nsamples << " < " << getWindowsize() << ")" << std::endl;
return;
}
int fftsize = mfcc->getfftlength();
vector<double> cc(ncoeff);
for (int i = 0; i < ncoeff; ++i) cc[i] = 0.0;
const double *psource = samples;
int pcount = nsamples;
if (decimator) {
pcount = nsamples / decimator->getFactor();
double *decout = new double[pcount];
decimator->process(samples, decout);
psource = decout;
}
int origin = 0;
int frames = 0;
double *frame = new double[fftsize];
double *ccout = new double[ncoeff];
while (origin <= pcount) {
// always need at least one fft window per block, but after
// that we want to avoid having any incomplete ones
if (origin > 0 && origin + fftsize >= pcount) break;
for (int i = 0; i < fftsize; ++i) {
if (origin + i < pcount) {
frame[i] = psource[origin + i];
} else {
frame[i] = 0.0;
}
}
mfcc->process(frame, ccout);
for (int i = 0; i < ncoeff; ++i) {
cc[i] += ccout[i];
}
++frames;
origin += fftsize/2;
}
delete [] ccout;
delete [] frame;
for (int i = 0; i < ncoeff; ++i) {
cc[i] /= frames;
}
if (decimator) delete[] psource;
features.push_back(cc);
}
void ClusterMeltSegmenter::segment(int m)
{
nclusters = m;
segment();
}
void ClusterMeltSegmenter::setFeatures(const vector<vector<double> >& f)
{
features = f;
featureType = FEATURE_TYPE_UNKNOWN;
}
void ClusterMeltSegmenter::segment()
{
delete constq;
constq = 0;
delete mfcc;
mfcc = 0;
delete decimator;
decimator = 0;
if (features.size() < histogramLength) return;
/*
std::cerr << "ClusterMeltSegmenter::segment: have " << features.size()
<< " features with " << features[0].size() << " coefficients (ncoeff = " << ncoeff << ", ncomponents = " << ncomponents << ")" << std::endl;
*/
// copy the features to a native array and use the existing C segmenter...
double** arrFeatures = new double*[features.size()];
for (int i = 0; i < features.size(); i++)
{
if (featureType == FEATURE_TYPE_UNKNOWN) {
arrFeatures[i] = new double[features[0].size()];
for (int j = 0; j < features[0].size(); j++)
arrFeatures[i][j] = features[i][j];
} else {
arrFeatures[i] = new double[ncoeff+1]; // allow space for the normalised envelope
for (int j = 0; j < ncoeff; j++)
arrFeatures[i][j] = features[i][j];
}
}
q = new int[features.size()];
if (featureType == FEATURE_TYPE_UNKNOWN ||
featureType == FEATURE_TYPE_MFCC)
cluster_segment(q, arrFeatures, features.size(), features[0].size(), nHMMStates, histogramLength,
nclusters, neighbourhoodLimit);
else
constq_segment(q, arrFeatures, features.size(), nbins, ncoeff, featureType,
nHMMStates, histogramLength, nclusters, neighbourhoodLimit);
// convert the cluster assignment sequence to a segmentation
makeSegmentation(q, features.size());
// de-allocate arrays
delete [] q;
for (int i = 0; i < features.size(); i++)
delete [] arrFeatures[i];
delete [] arrFeatures;
// clear the features
clear();
}
void ClusterMeltSegmenter::makeSegmentation(int* q, int len)
{
segmentation.segments.clear();
segmentation.nsegtypes = nclusters;
segmentation.samplerate = samplerate;
Segment segment;
segment.start = 0;
segment.type = q[0];
for (int i = 1; i < len; i++)
{
if (q[i] != q[i-1])
{
segment.end = i * getHopsize();
segmentation.segments.push_back(segment);
segment.type = q[i];
segment.start = segment.end;
}
}
segment.end = len * getHopsize();
segmentation.segments.push_back(segment);
}