annotate NNLSChroma.cpp @ 4:266d23a41cdc matthiasm-plugin

tested almost finished plugin, chord est with mode filter

#include "NNLSChroma.h"
#include <cmath>
#include <list>
#include <iostream>
#include <fstream>
#include <sstream>
#include <cassert>
#include <cstdio>
#include "nnls.h"
// #include "cblas.h"
#include "chorddict.cpp"
using namespace std;

const float sinvalue = 0.866025404;
const float cosvalue = -0.5;
const float hammingwind[19] = {0.0082, 0.0110, 0.0191, 0.0316, 0.0470, 0.0633, 0.0786, 0.0911, 0.0992, 0.1020, 0.0992, 0.0911, 0.0786, 0.0633, 0.0470, 0.0316, 0.0191, 0.0110, 0.0082};
const float basswindow[] = {0.001769, 0.015848, 0.043608, 0.084265, 0.136670, 0.199341, 0.270509, 0.348162, 0.430105, 0.514023, 0.597545, 0.678311, 0.754038, 0.822586, 0.882019, 0.930656, 0.967124, 0.990393, 0.999803, 0.995091, 0.976388, 0.944223, 0.899505, 0.843498, 0.777785, 0.704222, 0.624888, 0.542025, 0.457975, 0.375112, 0.295778, 0.222215, 0.156502, 0.100495, 0.055777, 0.023612, 0.004909, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.000000};
const float treblewindow[] = {0.000350, 0.003144, 0.008717, 0.017037, 0.028058, 0.041719, 0.057942, 0.076638, 0.097701, 0.121014, 0.146447, 0.173856, 0.203090, 0.233984, 0.266366, 0.300054, 0.334860, 0.370590, 0.407044, 0.444018, 0.481304, 0.518696, 0.555982, 0.592956, 0.629410, 0.665140, 0.699946, 0.733634, 0.766016, 0.796910, 0.826144, 0.853553, 0.878986, 0.902299, 0.923362, 0.942058, 0.958281, 0.971942, 0.982963, 0.991283, 0.996856, 0.999650, 0.999650, 0.996856, 0.991283, 0.982963, 0.971942, 0.958281, 0.942058, 0.923362, 0.902299, 0.878986, 0.853553, 0.826144, 0.796910, 0.766016, 0.733634, 0.699946, 0.665140, 0.629410, 0.592956, 0.555982, 0.518696, 0.481304, 0.444018, 0.407044, 0.370590, 0.334860, 0.300054, 0.266366, 0.233984, 0.203090, 0.173856, 0.146447, 0.121014, 0.097701, 0.076638, 0.057942, 0.041719, 0.028058, 0.017037, 0.008717, 0.003144, 0.000350};
const char* notenames[24] = {"A  (bass)","Bb (bass)","B  (bass)","C  (bass)","C# (bass)","D  (bass)","Eb (bass)","E  (bass)","F  (bass)","F# (bass)","G  (bass)","Ab (bass)",
"A","Bb","B","C","C#","D","Eb","E","F","F#","G","Ab"};
const vector<float> hw(hammingwind, hammingwind+19);
const int nNote = 256;

/** Special Convolution
special convolution is as long as the convolvee, i.e. the first argument. in the valid core part of the 
convolution it contains the usual convolution values, but the pads at the beginning (ending) have the same values
as the first (last) valid convolution bin.
**/

const bool debug_on = false;

vector<float> SpecialConvolution(vector<float> convolvee, vector<float> kernel)
{
    float s;
    int m, n;
    int lenConvolvee = convolvee.size();
    int lenKernel = kernel.size();

    vector<float> Z(256,0);
    assert(lenKernel % 2 != 0); // no exception handling !!!
    
    for (n = lenKernel - 1; n < lenConvolvee; n++) {
    	s=0.0;
    	for (m = 0; m < lenKernel; m++) {
            // cerr << "m = " << m << ", n = " << n << ", n-m = " << (n-m) << '\n';
            s += convolvee[n-m] * kernel[m];
            // if (debug_on) cerr << "--> s = " << s << '\n';
    	}
        // cerr << n - lenKernel/2 << endl;
        Z[n -lenKernel/2] = s;
    }
    
    // fill upper and lower pads
    for (n = 0; n < lenKernel/2; n++) Z[n] = Z[lenKernel/2];    
    for (n = lenConvolvee; n < lenConvolvee +lenKernel/2; n++) Z[n - lenKernel/2] = 
        Z[lenConvolvee - lenKernel/2 -  1];
    return Z;
}

// vector<float> FftBin2Frequency(vector<float> binnumbers, int fs, int blocksize)
// {
// 	vector<float> freq(binnumbers.size, 0.0);
// 	for (unsigned i = 0; i < binnumbers.size; ++i) {
// 		freq[i] = (binnumbers[i]-1.0) * fs * 1.0 / blocksize;	
// 	}
// 	return freq;
// }

float cospuls(float x, float centre, float width) 
{
	float recipwidth = 1.0/width;
	if (abs(x - centre) <= 0.5 * width) {
		return cos((x-centre)*2*M_PI*recipwidth)*.5+.5;
	}
	return 0.0;
}

float pitchCospuls(float x, float centre, int binsperoctave) 
{
	float warpedf = -binsperoctave * (log2(centre) - log2(x));
	float out = cospuls(warpedf, 0.0, 2.0);
	// now scale to correct for note density
	float c = log(2.0)/binsperoctave;
	if (x > 0) {
		out = out / (c * x);
	} else {
		out = 0;
	}
	return out;
}

bool logFreqMatrix(int fs, int blocksize, float *outmatrix) {
	
	int binspersemitone = 3; // this must be 3
	int minoctave = 0; // this must be 0
	int maxoctave = 7; // this must be 7
	int oversampling = 80;
	
	// linear frequency vector
	vector<float> fft_f;
	for (int i = 0; i < blocksize/2; ++i) {
		fft_f.push_back(i * (fs * 1.0 / blocksize));
	}
	float fft_width = fs * 2.0 / blocksize;
	
	// linear oversampled frequency vector
	vector<float> oversampled_f;
	for (unsigned int i = 0; i < oversampling * blocksize/2; ++i) {
		oversampled_f.push_back(i * ((fs * 1.0 / blocksize) / oversampling));
	}
	
	// pitch-spaced frequency vector
	int minMIDI = 21 + minoctave * 12 - 1; // this includes one additional semitone!
	int maxMIDI = 21 + maxoctave * 12; // this includes one additional semitone!
	vector<float> cq_f;
	float oob = 1.0/binspersemitone; // one over binspersemitone
	cq_f.push_back(440 * pow(2.0,0.083333 * (minMIDI-69))); // 0.083333 is approx 1/12
	cq_f.push_back(440 * pow(2.0,0.083333 * (minMIDI+oob-69)));
	for (int i = minMIDI + 1; i < maxMIDI; ++i) {
		for (int k = -1; k < 2; ++k)	 {
			cq_f.push_back(440 * pow(2.0,0.083333333333 * (i+oob*k-69)));
		}
	}
	cq_f.push_back(440 * pow(2.0,0.083333 * (minMIDI-oob-69)));
	cq_f.push_back(440 * pow(2.0,0.083333 * (maxMIDI-69)));

	int nFFT = fft_f.size();
	
	vector<float> fft_activation;
	for (int iOS = 0; iOS < 2 * oversampling; ++iOS) {
		float cosp = cospuls(oversampled_f[iOS],fft_f[1],fft_width);
		fft_activation.push_back(cosp);
		// cerr << cosp << endl;
	}
	
	float cq_activation;
	for (int iFFT = 1; iFFT < nFFT; ++iFFT) {
		// find frequency stretch where the oversampled vector can be non-zero (i.e. in a window of width fft_width around the current frequency)
		int curr_start = oversampling * iFFT - oversampling;
		int curr_end = oversampling * iFFT + oversampling; // don't know if I should add "+1" here
		// cerr << oversampled_f[curr_start] << " " << fft_f[iFFT] << " " << oversampled_f[curr_end] << endl;
		for (unsigned iCQ = 0; iCQ < cq_f.size(); ++iCQ) {
			outmatrix[iFFT + nFFT * iCQ] = 0;
			if (cq_f[iCQ] * pow(2.0, 0.084) + fft_width > fft_f[iFFT] && cq_f[iCQ] * pow(2.0, -0.084 * 2) - fft_width < fft_f[iFFT]) { // within a generous neighbourhood
				for (int iOS = curr_start; iOS < curr_end; ++iOS) {
					cq_activation = pitchCospuls(oversampled_f[iOS],cq_f[iCQ],binspersemitone*12);
					// cerr << oversampled_f[iOS] << " " << cq_f[iCQ] << " " << cq_activation << endl;
					outmatrix[iFFT + nFFT * iCQ] += cq_activation * fft_activation[iOS-curr_start];
				}				
				// if (iCQ == 1 || iCQ == 2) {
				// 	cerr << " " << outmatrix[iFFT + nFFT * iCQ] << endl;
				// }
			}
		}
	}
	return true;	
}

bool dictionaryMatrix(float* dm) {
	int binspersemitone = 3; // this must be 3
	int minoctave = 0; // this must be 0
	int maxoctave = 7; // this must be 7
	float s_param = 0.7;
	
	// pitch-spaced frequency vector
	int minMIDI = 21 + minoctave * 12 - 1; // this includes one additional semitone!
	int maxMIDI = 21 + maxoctave * 12; // this includes one additional semitone!
	vector<float> cq_f;
	float oob = 1.0/binspersemitone; // one over binspersemitone
	cq_f.push_back(440 * pow(2.0,0.083333 * (minMIDI-69))); // 0.083333 is approx 1/12
	cq_f.push_back(440 * pow(2.0,0.083333 * (minMIDI+oob-69)));
	for (int i = minMIDI + 1; i < maxMIDI; ++i) {
		for (int k = -1; k < 2; ++k)	 {
			cq_f.push_back(440 * pow(2.0,0.083333333333 * (i+oob*k-69)));
		}
	}
	cq_f.push_back(440 * pow(2.0,0.083333 * (minMIDI-oob-69)));
	cq_f.push_back(440 * pow(2.0,0.083333 * (maxMIDI-69)));

	float curr_f;
	float floatbin;
	float curr_amp;
	// now for every combination calculate the matrix element
	for (unsigned iOut = 0; iOut < 12 * (maxoctave - minoctave); ++iOut) {
		// cerr << iOut << endl;
		for (unsigned iHarm = 1; iHarm <= 20; ++iHarm) {
			curr_f = 440 * pow(2,(minMIDI-69+iOut)*1.0/12) * iHarm;
			// if (curr_f > cq_f[nNote-1])  break;
			floatbin = ((iOut + 1) * binspersemitone + 1) + binspersemitone * 12 * log2(iHarm);
			// cerr << floatbin << endl;
			curr_amp = pow(s_param,float(iHarm-1));
			// cerr << "curramp" << curr_amp << endl;
			for (unsigned iNote = 0; iNote < nNote; ++iNote) {
				if (abs(iNote+1.0-floatbin)<2) {
					dm[iNote  + 256 * iOut] += cospuls(iNote+1.0, floatbin, binspersemitone + 0.0) * curr_amp;
					// dm[iNote + nNote * iOut] += 1 * curr_amp;
				}
			}
		}
	}


}


NNLSChroma::NNLSChroma(float inputSampleRate) :
  Plugin(inputSampleRate),
  m_fl(0),
  m_blockSize(0),
  m_stepSize(0),
  m_lengthOfNoteIndex(0),
  m_meanTuning0(0),
  m_meanTuning1(0),
  m_meanTuning2(0),
  m_localTuning0(0),
  m_localTuning1(0),
  m_localTuning2(0),
  m_paling(1.0),
  m_preset(0.0),
  m_localTuning(0),
  m_kernelValue(0),
  m_kernelFftIndex(0),
  m_kernelNoteIndex(0),
  m_dict(0),
  m_tuneLocal(false),
  m_dictID(0)
{
	if (debug_on) cerr << "--> NNLSChroma" << endl;
	m_dict = new float[nNote * 84];
	for (unsigned i = 0; i < nNote * 84; ++i) m_dict[i] = 0.0;
	dictionaryMatrix(m_dict);
}


NNLSChroma::~NNLSChroma()
{
		if (debug_on) cerr << "--> ~NNLSChroma" << endl;
		delete [] m_dict;
}

string
NNLSChroma::getIdentifier() const
{
	if (debug_on) cerr << "--> getIdentifier" << endl;
    return "nnls_chroma";
}

string
NNLSChroma::getName() const
{
		if (debug_on) cerr << "--> getName" << endl;
    return "NNLS Chroma";
}

string
NNLSChroma::getDescription() const
{
    // Return something helpful here!
	if (debug_on) cerr << "--> getDescription" << endl;
    return "This plugin provides a number of features derived from a log-frequency amplitude spectrum (LAS) of the DFT: the LAS itself, a standard-tuned version thereof (the local and global tuning estimates can are also be output), an approximate transcription to semitone activation using non-linear least squares (NNLS). Furthermore chroma features and a simple chord estimate derived from this NNLS semitone transcription.";
}

string
NNLSChroma::getMaker() const
{
		if (debug_on) cerr << "--> getMaker" << endl;
    // Your name here
    return "Matthias Mauch";
}

int
NNLSChroma::getPluginVersion() const
{
		if (debug_on) cerr << "--> getPluginVersion" << endl;
    // Increment this each time you release a version that behaves
    // differently from the previous one
    return 1;
}

string
NNLSChroma::getCopyright() const
{
		if (debug_on) cerr << "--> getCopyright" << endl;
    // This function is not ideally named.  It does not necessarily
    // need to say who made the plugin -- getMaker does that -- but it
    // should indicate the terms under which it is distributed.  For
    // example, "Copyright (year). All Rights Reserved", or "GPL"
    return "Copyright (2010). All rights reserved.";
}

NNLSChroma::InputDomain
NNLSChroma::getInputDomain() const
{
		if (debug_on) cerr << "--> getInputDomain" << endl;
    return FrequencyDomain;
}

size_t
NNLSChroma::getPreferredBlockSize() const
{
		if (debug_on) cerr << "--> getPreferredBlockSize" << endl;
    return 16384; // 0 means "I can handle any block size"
}

size_t 
NNLSChroma::getPreferredStepSize() const
{
		if (debug_on) cerr << "--> getPreferredStepSize" << endl;
    return 2048; // 0 means "anything sensible"; in practice this
              // means the same as the block size for TimeDomain
              // plugins, or half of it for FrequencyDomain plugins
}

size_t
NNLSChroma::getMinChannelCount() const
{
	if (debug_on) cerr << "--> getMinChannelCount" << endl;
    return 1;
}

size_t
NNLSChroma::getMaxChannelCount() const
{
		if (debug_on) cerr << "--> getMaxChannelCount" << endl;
    return 1;
}

NNLSChroma::ParameterList
NNLSChroma::getParameterDescriptors() const
{
		if (debug_on) cerr << "--> getParameterDescriptors" << endl;
    ParameterList list;

    ParameterDescriptor d3;
    d3.identifier = "preset";
    d3.name = "preset";
    d3.description = "Spectral paling: no paling - 0; whitening - 1.";
    d3.unit = "";
	d3.isQuantized = true;
	d3.quantizeStep = 1;
    d3.minValue = 0.0;
    d3.maxValue = 3.0;
    d3.defaultValue = 0.0;
    d3.valueNames.push_back("polyphonic pop");
	d3.valueNames.push_back("polyphonic pop (fast)");
    d3.valueNames.push_back("solo keyboard");
	d3.valueNames.push_back("manual");
    list.push_back(d3);

    // ParameterDescriptor d0;
    //  d0.identifier = "notedict";
    //  d0.name = "note dictionary";
    //  d0.description = "Notes in different note dictionaries differ by their spectral shapes.";
    //  d0.unit = "";
    //  d0.minValue = 0;
    //  d0.maxValue = 1;
    //  d0.defaultValue = 0;
    //  d0.isQuantized = true;
    //  d0.valueNames.push_back("s = 0.6");
    //  d0.valueNames.push_back("no NNLS");
    //  d0.quantizeStep = 1.0;
    //  list.push_back(d0);

    ParameterDescriptor d1;
    d1.identifier = "tuningmode";
    d1.name = "tuning mode";
    d1.description = "Tuning can be performed locally or on the whole extraction segment. Local tuning is only advisable when the tuning is likely to change over the audio, for example in podcasts, or in a cappella singing.";
    d1.unit = "";
    d1.minValue = 0;
    d1.maxValue = 1;
    d1.defaultValue = 0;
    d1.isQuantized = true;
    d1.valueNames.push_back("global tuning");
    d1.valueNames.push_back("local tuning");
    d1.quantizeStep = 1.0;
    list.push_back(d1);

	//     ParameterDescriptor d2;
	//     d2.identifier = "paling";
	//     d2.name = "spectral paling";
	//     d2.description = "Spectral paling: no paling - 0; whitening - 1.";
	//     d2.unit = "";
	// d2.isQuantized = true;
	// // d2.quantizeStep = 0.1;
	//     d2.minValue = 0.0;
	//     d2.maxValue = 1.0;
	//     d2.defaultValue = 1.0;
	//     d2.isQuantized = false;
	//     list.push_back(d2);

    return list;
}

float
NNLSChroma::getParameter(string identifier) const
{
	if (debug_on) cerr << "--> getParameter" << endl;
    if (identifier == "notedict") {
        return m_dictID; 
    }
    
    if (identifier == "paling") {
        return m_paling; 
    }
    
    if (identifier == "tuningmode") {
        if (m_tuneLocal) {
            return 1.0;
        } else {
            return 0.0;
        }
    }
	if (identifier == "preset") {
		return m_preset;
    }
    return 0;
    
}

void
NNLSChroma::setParameter(string identifier, float value) 
{
	if (debug_on) cerr << "--> setParameter" << endl;
    if (identifier == "notedict") {
        m_dictID = (int) value;
    }
    
    if (identifier == "paling") {
        m_paling = value;
    }
    
    if (identifier == "tuningmode") {
        m_tuneLocal = (value > 0) ? true : false;
        // cerr << "m_tuneLocal :" << m_tuneLocal << endl;
    }
    if (identifier == "preset") {
        m_preset = value;
		if (m_preset == 0.0) {
			m_tuneLocal = false;
			m_paling = 1.0;
			m_dictID = 0.0;
		}
		if (m_preset == 1.0) {
			m_tuneLocal = false;
			m_paling = 1.0;
			m_dictID = 1.0;
		}
		if (m_preset == 2.0) {
			m_tuneLocal = false;
			m_paling = 0.7;
			m_dictID = 0.0;
		}
    }
}

NNLSChroma::ProgramList
NNLSChroma::getPrograms() const
{
		if (debug_on) cerr << "--> getPrograms" << endl;
    ProgramList list;

    // If you have no programs, return an empty list (or simply don't
    // implement this function or getCurrentProgram/selectProgram)

    return list;
}

string
NNLSChroma::getCurrentProgram() const
{
		if (debug_on) cerr << "--> getCurrentProgram" << endl;
    return ""; // no programs
}

void
NNLSChroma::selectProgram(string name)
{
		if (debug_on) cerr << "--> selectProgram" << endl;
}


NNLSChroma::OutputList
NNLSChroma::getOutputDescriptors() const
{
		if (debug_on) cerr << "--> getOutputDescriptors" << endl;
    OutputList list;
    
    // Make chroma names for the binNames property
    vector<string> chromanames;
    vector<string> bothchromanames;
    for (int iNote = 0; iNote < 24; iNote++) {
        bothchromanames.push_back(notenames[iNote]);
        if (iNote < 12) {
            chromanames.push_back(notenames[iNote]);
        }
    }
    
	// int nNote = 84;

    // See OutputDescriptor documentation for the possibilities here.
    // Every plugin must have at least one output.

    OutputDescriptor d0;
    d0.identifier = "tuning";
    d0.name = "Tuning";
    d0.description = "The concert pitch.";
    d0.unit = "Hz";
    d0.hasFixedBinCount = true;
    d0.binCount = 0;
    d0.hasKnownExtents = true;
	d0.minValue = 427.47;
	d0.maxValue = 452.89;
    d0.isQuantized = false;
    d0.sampleType = OutputDescriptor::VariableSampleRate;
    d0.hasDuration = false;
    list.push_back(d0);
	
	OutputDescriptor d1;
    d1.identifier = "logfreqspec";
    d1.name = "Log-Frequency Spectrum";
    d1.description = "A Log-Frequency Spectrum (constant Q) that is obtained by cosine filter mapping.";
    d1.unit = "";
    d1.hasFixedBinCount = true;
    d1.binCount = nNote;
    d1.hasKnownExtents = false;
    d1.isQuantized = false;
    d1.sampleType = OutputDescriptor::FixedSampleRate;
    d1.hasDuration = false;
    d1.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
    list.push_back(d1);

	OutputDescriptor d2;
    d2.identifier = "tunedlogfreqspec";
    d2.name = "Tuned Log-Frequency Spectrum";
    d2.description = "A Log-Frequency Spectrum (constant Q) that is obtained by cosine filter mapping, then its tuned using the estimated tuning frequency.";
    d2.unit = "";
    d2.hasFixedBinCount = true;
    d2.binCount = 256;
    d2.hasKnownExtents = false;
    d2.isQuantized = false;
    d2.sampleType = OutputDescriptor::FixedSampleRate;
    d2.hasDuration = false;
    d2.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
    list.push_back(d2);
    
    OutputDescriptor d3;
    d3.identifier = "semitonespectrum";
    d3.name = "Semitone Spectrum";
    d3.description = "A semitone-spaced log-frequency spectrum derived from the third-of-a-semitone-spaced tuned log-frequency spectrum.";
    d3.unit = "";
    d3.hasFixedBinCount = true;
    d3.binCount = 84;
    d3.hasKnownExtents = false;
    d3.isQuantized = false;
    d3.sampleType = OutputDescriptor::FixedSampleRate;
    d3.hasDuration = false;
    d3.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
    list.push_back(d3);
    
    OutputDescriptor d4;
    d4.identifier = "chroma";
    d4.name = "Chromagram";
    d4.description = "Tuning-adjusted chromagram from NNLS soft transcription, with an emphasis on the medium note range.";
    d4.unit = "";
    d4.hasFixedBinCount = true;
    d4.binCount = 12;
    d4.binNames = chromanames;
    d4.hasKnownExtents = false;
    d4.isQuantized = false;
    d4.sampleType = OutputDescriptor::FixedSampleRate;
    d4.hasDuration = false;
    d4.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
    list.push_back(d4);
    
    OutputDescriptor d5;
    d5.identifier = "basschroma";
    d5.name = "Bass Chromagram";
    d5.description = "Tuning-adjusted bass chromagram from NNLS soft transcription, with an emphasis on the bass note range.";
    d5.unit = "";
    d5.hasFixedBinCount = true;
    d5.binCount = 12;
    d5.binNames = chromanames;
    d5.hasKnownExtents = false;
    d5.isQuantized = false;
    d5.sampleType = OutputDescriptor::FixedSampleRate;
    d5.hasDuration = false;
    d5.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
    list.push_back(d5);
    
    OutputDescriptor d6;
    d6.identifier = "bothchroma";
    d6.name = "Chromagram and Bass Chromagram";
    d6.description = "Tuning-adjusted chromagram and bass chromagram (stacked on top of each other) from NNLS soft transcription.";
    d6.unit = "";
    d6.hasFixedBinCount = true;
    d6.binCount = 24;
    d6.binNames = bothchromanames;
    d6.hasKnownExtents = false;
    d6.isQuantized = false;
    d6.sampleType = OutputDescriptor::FixedSampleRate;
    d6.hasDuration = false;
    d6.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
    list.push_back(d6);
    
    OutputDescriptor d7;
    d7.identifier = "simplechord";
    d7.name = "Simple Chord Estimate";
    d7.description = "A simple chord estimate based on the inner product of chord templates with the smoothed chroma.";
    d7.unit = "";
    d7.hasFixedBinCount = true;
    d7.binCount = 0;
    d7.hasKnownExtents = false;
    d7.isQuantized = false;
    d7.sampleType = OutputDescriptor::VariableSampleRate;
    d7.hasDuration = false;
    d7.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
    list.push_back(d7);
    
  	//   OutputDescriptor d8;
  	//     d8.identifier = "inconsistency";
  	//     d8.name = "Harmonic inconsistency value";
  	//     d8.description = "Harmonic inconsistency. Indicates music if low, non-music or speech when high.";
  	//     d8.unit = "";
  	//     d8.hasFixedBinCount = true;
  	//     d8.binCount = 1;
  	//     d8.hasKnownExtents = false;
  	//     d8.isQuantized = false;
  	//     d8.sampleType = OutputDescriptor::FixedSampleRate;
  	//     d8.hasDuration = false;
  	//     d8.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
  	//     list.push_back(d8);
  	//     
  	//     OutputDescriptor d9;
  	//     d9.identifier = "inconsistencysegment";
  	//     d9.name = "Harmonic inconsistency segmenter";
  	//     d9.description = "Segments the audio based on the harmonic inconsistency value into speech and music.";
  	//     d9.unit = "";
  	//     d9.hasFixedBinCount = true;
  	//     d9.binCount = 0;
  	//     d9.hasKnownExtents = true;
  	//     d9.minValue = 0.1;
  	// d9.maxValue = 0.9;
  	//     d9.isQuantized = false;
  	//     d9.sampleType = OutputDescriptor::VariableSampleRate;
  	//     d9.hasDuration = false;
  	//     d9.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
  	//     list.push_back(d9);
  	// 
  	OutputDescriptor d10;
  	    d10.identifier = "localtuning";
  	    d10.name = "Local tuning";
  	    d10.description = "Tuning based on the history up to this timestamp.";
  	    d10.unit = "Hz";
  	    d10.hasFixedBinCount = true;
  	    d10.binCount = 1;
  	    d10.hasKnownExtents = true;
		d10.minValue = 427.47;
  		d10.maxValue = 452.89;
  	    d10.isQuantized = false;
  	    d10.sampleType = OutputDescriptor::FixedSampleRate;
  	    d10.hasDuration = false;
  	    // d10.sampleRate = (m_stepSize == 0) ? m_inputSampleRate/2048 : m_inputSampleRate/m_stepSize;
  	    list.push_back(d10);
  
    return list;
}


bool
NNLSChroma::initialise(size_t channels, size_t stepSize, size_t blockSize)
{	
	if (debug_on) {
		cerr << "--> initialise";
	}
	
    if (channels < getMinChannelCount() ||
	channels > getMaxChannelCount()) return false;
    m_blockSize = blockSize;
    m_stepSize = stepSize;
    frameCount = 0;
	int tempn = 256 * m_blockSize/2;
	// cerr << "length of tempkernel : " <<  tempn << endl;
	float *tempkernel;

	tempkernel = new float[tempn];

	logFreqMatrix(m_inputSampleRate, m_blockSize, tempkernel);
	m_kernelValue.clear();
	m_kernelFftIndex.clear();
	m_kernelNoteIndex.clear();
	int countNonzero = 0;
	for (unsigned iNote = 0; iNote < nNote; ++iNote) { // I don't know if this is wise: manually making a sparse matrix
		for (unsigned iFFT = 0; iFFT < blockSize/2; ++iFFT) {
			if (tempkernel[iFFT + blockSize/2 * iNote] > 0) {
				m_kernelValue.push_back(tempkernel[iFFT + blockSize/2 * iNote]);
				if (tempkernel[iFFT + blockSize/2 * iNote] > 0) {
					countNonzero++;
				}
				m_kernelFftIndex.push_back(iFFT);
				m_kernelNoteIndex.push_back(iNote);				
			}
		}
	}
	// cerr << "nonzero count : " << countNonzero << endl;
	delete [] tempkernel;
	ofstream myfile;
	myfile.open ("matrix.txt");
    // myfile << "Writing this to a file.\n";	
	for (int i = 0; i < nNote * 84; ++i) {
		myfile << m_dict[i] << endl;		
	}
    myfile.close();
    return true;
}

void
NNLSChroma::reset()
{
	if (debug_on) cerr << "--> reset";
	
    // Clear buffers, reset stored values, etc
	frameCount = 0;
	m_dictID = 0;
	m_fl.clear();
	m_meanTuning0 = 0;
	m_meanTuning1 = 0;
	m_meanTuning2 = 0;
	m_localTuning0 = 0;
	m_localTuning1 = 0;
	m_localTuning2 = 0;
	m_localTuning.clear();
}

NNLSChroma::FeatureSet
NNLSChroma::process(const float *const *inputBuffers, Vamp::RealTime timestamp)
{   
	if (debug_on) cerr << "--> process" << endl;
	    
	frameCount++;   
	float *magnitude = new float[m_blockSize/2];
	
	Feature f10; // local tuning
	f10.hasTimestamp = true;
	f10.timestamp = timestamp;
	const float *fbuf = inputBuffers[0];	
	
	// make magnitude
	for (size_t iBin = 0; iBin < m_blockSize/2; iBin++) {
		magnitude[iBin] = sqrt(fbuf[2 * iBin] * fbuf[2 * iBin] + 
			fbuf[2 * iBin + 1] * fbuf[2 * iBin + 1]);
	}
		
	// note magnitude mapping using pre-calculated matrix
	float *nm  = new float[nNote]; // note magnitude
	for (size_t iNote = 0; iNote < nNote; iNote++) {
		nm[iNote] = 0; // initialise as 0
	}
	int binCount = 0;
	for (vector<float>::iterator it = m_kernelValue.begin(); it != m_kernelValue.end(); ++it) {
		// cerr << ".";
		nm[m_kernelNoteIndex[binCount]] += magnitude[m_kernelFftIndex[binCount]] * m_kernelValue[binCount];
		// cerr << m_kernelFftIndex[binCount] << " -- " << magnitude[m_kernelFftIndex[binCount]] << " -- "<< m_kernelValue[binCount] << endl;
		binCount++;	
	}
	// cerr << nm[20];
	// cerr << endl;
	
	
    float one_over_N = 1.0/frameCount;
    // update means of complex tuning variables
    m_meanTuning0 *= float(frameCount-1)*one_over_N;
    m_meanTuning1 *= float(frameCount-1)*one_over_N;
    m_meanTuning2 *= float(frameCount-1)*one_over_N;
	
    for (int iTone = 0; iTone < 160; iTone = iTone + 3) {
        m_meanTuning0 += nm[iTone + 0]*one_over_N;
    	m_meanTuning1 += nm[iTone + 1]*one_over_N;
    	m_meanTuning2 += nm[iTone + 2]*one_over_N;
		float ratioOld = 0.997;
        m_localTuning0 *= ratioOld; m_localTuning0 += nm[iTone + 0] * (1 - ratioOld);
        m_localTuning1 *= ratioOld; m_localTuning1 += nm[iTone + 1] * (1 - ratioOld);
        m_localTuning2 *= ratioOld; m_localTuning2 += nm[iTone + 2] * (1 - ratioOld);
    }
	
    // if (m_tuneLocal) {
    	// local tuning
        float localTuningImag = sinvalue * m_localTuning1 - sinvalue * m_localTuning2;
        float localTuningReal = m_localTuning0 + cosvalue * m_localTuning1 + cosvalue * m_localTuning2;
        float normalisedtuning = atan2(localTuningImag, localTuningReal)/(2*M_PI);
        m_localTuning.push_back(normalisedtuning);
        float tuning440 = 440 * pow(2,normalisedtuning/12);
        f10.values.push_back(tuning440);
		// cerr << tuning440 << endl;
    // }
    
	Feature f1; // logfreqspec
	f1.hasTimestamp = true;
    f1.timestamp = timestamp;
	for (size_t iNote = 0; iNote < nNote; iNote++) {
		f1.values.push_back(nm[iNote]);
	}
	
	FeatureSet fs;
	fs[1].push_back(f1);
    fs[8].push_back(f10);

    // deletes
    delete[] magnitude;
    delete[] nm;

    m_fl.push_back(f1); // remember note magnitude for getRemainingFeatures
	return fs;	
}

NNLSChroma::FeatureSet
NNLSChroma::getRemainingFeatures()
{
	if (debug_on) cerr << "--> getRemainingFeatures" << endl;
	FeatureSet fsOut;
	if (m_fl.size() == 0) return fsOut;
	// 
	/**  Calculate Tuning
		calculate tuning from (using the angle of the complex number defined by the 
		cumulative mean real and imag values)
		**/
		float meanTuningImag = sinvalue * m_meanTuning1 - sinvalue * m_meanTuning2;
		    float meanTuningReal = m_meanTuning0 + cosvalue * m_meanTuning1 + cosvalue * m_meanTuning2;
		    float cumulativetuning = 440 * pow(2,atan2(meanTuningImag, meanTuningReal)/(24*M_PI));
		    float normalisedtuning = atan2(meanTuningImag, meanTuningReal)/(2*M_PI);
		    int intShift = floor(normalisedtuning * 3);
		    float intFactor = normalisedtuning * 3 - intShift; // intFactor is a really bad name for this
		    
		    char buffer0 [50];
		
		    sprintf(buffer0, "estimated tuning: %0.1f Hz", cumulativetuning);
		    
		    // cerr << "normalisedtuning: " << normalisedtuning << '\n';
		    
		    // push tuning to FeatureSet fsOut
		Feature f0; // tuning
		f0.hasTimestamp = true;
		    f0.timestamp = Vamp::RealTime::frame2RealTime(0, lrintf(m_inputSampleRate));;
		    f0.label = buffer0;
		    fsOut[0].push_back(f0);  
		    
		    /** Tune Log-Frequency Spectrogram
		    calculate a tuned log-frequency spectrogram (f2): use the tuning estimated above (kinda f0) to 
		    perform linear interpolation on the existing log-frequency spectrogram (kinda f1).
		    **/    
		
		    float tempValue = 0;
		    float dbThreshold = 0; // relative to the background spectrum
		    float thresh = pow(10,dbThreshold/20);
		    // cerr << "tune local ? " << m_tuneLocal << endl;
		    int count = 0;
		
		    for (FeatureList::iterator i = m_fl.begin(); i != m_fl.end(); ++i) {
		        Feature f1 = *i;
		        Feature f2; // tuned log-frequency spectrum
		        f2.hasTimestamp = true;
		        f2.timestamp = f1.timestamp;
		        f2.values.push_back(0.0); f2.values.push_back(0.0); // set lower edge to zero
		
		        if (m_tuneLocal) {
		            intShift = floor(m_localTuning[count] * 3);
		            intFactor = m_localTuning[count] * 3 - intShift; // intFactor is a really bad name for this
		        }
		        
		        // cerr << intShift << " " << intFactor << endl;
		        
		        for (unsigned k = 2; k < f1.values.size() - 3; ++k) { // interpolate all inner bins
		            tempValue = f1.values[k + intShift] * (1-intFactor) + f1.values[k+intShift+1] * intFactor;
		            f2.values.push_back(tempValue);
		        }
		        
		        f2.values.push_back(0.0); f2.values.push_back(0.0); f2.values.push_back(0.0); // upper edge
		        vector<float> runningmean = SpecialConvolution(f2.values,hw);
		        vector<float> runningstd;
		        for (int i = 0; i < 256; i++) { // first step: squared values into vector (variance)
		            runningstd.push_back((f2.values[i] - runningmean[i]) * (f2.values[i] - runningmean[i]));
		        }
		        runningstd = SpecialConvolution(runningstd,hw); // second step convolve
		        for (int i = 0; i < 256; i++) { 
		            runningstd[i] = sqrt(runningstd[i]); // square root to finally have running std
		            if (runningstd[i] > 0) {
		                // f2.values[i] = (f2.values[i] / runningmean[i]) > thresh ? 
		                // 		                    (f2.values[i] - runningmean[i]) / pow(runningstd[i],m_paling) : 0;
						f2.values[i] = (f2.values[i] - runningmean[i]) > 0 ?
		                    (f2.values[i] - runningmean[i]) / pow(runningstd[i],m_paling) : 0;
		            }
		            if (f2.values[i] < 0) {
		                cerr << "ERROR: negative value in logfreq spectrum" << endl;
		            }
		        }
		        fsOut[2].push_back(f2);
		        count++;
		    }
	    
	    /** Semitone spectrum and chromagrams
	    Semitone-spaced log-frequency spectrum derived from the tuned log-freq spectrum above. the spectrum
	    is inferred using a non-negative least squares algorithm.
	    Three different kinds of chromagram are calculated, "treble", "bass", and "both" (which means 
	    bass and treble stacked onto each other).
	    **/
	    // taucs_ccs_matrix* A_original_ordering = taucs_construct_sorted_ccs_matrix(nnlsdict06, nnls_m, nnls_n);
	    
	    vector<vector<float> > chordogram;
		vector<vector<int> > scoreChordogram;
	    vector<float> oldchroma = vector<float>(12,0);
	    vector<float> oldbasschroma = vector<float>(12,0);
	    count = 0;
	
	    for (FeatureList::iterator it = fsOut[2].begin(); it != fsOut[2].end(); ++it) {
	        Feature f2 = *it; // logfreq spectrum
	        Feature f3; // semitone spectrum
	        Feature f4; // treble chromagram
	        Feature f5; // bass chromagram
	        Feature f6; // treble and bass chromagram
	
	        f3.hasTimestamp = true;
	        f3.timestamp = f2.timestamp;
	        
	        f4.hasTimestamp = true;
	        f4.timestamp = f2.timestamp;
	        
	        f5.hasTimestamp = true;
	        f5.timestamp = f2.timestamp;
	        
	        f6.hasTimestamp = true;
	        f6.timestamp = f2.timestamp;
	        
			float b[256];
	
	        bool some_b_greater_zero = false;
			float sumb = 0;
	        for (int i = 0; i < 256; i++) {
				// b[i] = m_dict[(256 * count + i) % (256 * 84)];
				b[i] = f2.values[i];
				sumb += b[i];
	            if (b[i] > 0) {
	                some_b_greater_zero = true;
	            }            
	        }
	    
	        // here's where the non-negative least squares algorithm calculates the note activation x
	
	        vector<float> chroma = vector<float>(12, 0);
	        vector<float> basschroma = vector<float>(12, 0);
			float currval;
			unsigned iSemitone = 0;
			
			if (some_b_greater_zero) {
				if (m_dictID == 1) {
					for (unsigned iNote = 2; iNote < nNote - 2; iNote += 3) {
						currval = 0;
						currval += b[iNote + 1 + -1] * 0.5;						
						currval += b[iNote + 1 +  0] * 1.0;						
						currval += b[iNote + 1 +  1] * 0.5;						
						f3.values.push_back(currval);
						chroma[iSemitone % 12] += currval * treblewindow[iSemitone];
						basschroma[iSemitone % 12] += currval * basswindow[iSemitone];
						iSemitone++;
					}
		        
				} else {
					float x[84+1000];
					for (int i = 1; i < 1084; ++i) x[i] = 1.0;
					// for (int i = 0; i < 84; ++i) {
					// 	x[i] = b[3*i+3];
					// }
				    float rnorm;
				    float w[84+1000];
				    float zz[84+1000];
				    int indx[84+1000];
				    int mode;
					float curr_dict[256*84];
					for (unsigned i = 0; i < 256 * 84; ++i) {
						curr_dict[i] = 1.0 * m_dict[i];
					}
					nnls(curr_dict, nNote, nNote, 84, b, x, &rnorm, w, zz, indx, &mode);
					for (unsigned iNote = 0; iNote < 84; ++iNote) {
						// for	(unsigned kNote = 0; kNote < 256; ++kNote) {
						// 						x[iNote] += m_dict[kNote + nNote * iNote] * b[kNote];
						// 					}					
						f3.values.push_back(x[iNote]);
						// cerr << mode << endl;
						chroma[iNote % 12] += x[iNote] * treblewindow[iNote];
						basschroma[iNote % 12] += x[iNote] * basswindow[iNote];
						// iSemitone++;
					}
				}	
			}
	
	        f4.values = chroma;
	        f5.values = basschroma;
	        chroma.insert(chroma.begin(), basschroma.begin(), basschroma.end()); // just stack the both chromas 
	        f6.values = chroma; 
	        
	        // local chord estimation
	        vector<float> currentChordSalience;
	        float tempchordvalue = 0;
	        float sumchordvalue = 0;
	        int nChord = nChorddict / 24;
	        for (int iChord = 0; iChord < nChord; iChord++) {
	            tempchordvalue = 0;
	            for (int iBin = 0; iBin < 12; iBin++) {
	                tempchordvalue += chorddict[24 * iChord + iBin] * chroma[iBin];
	            }
	            for (int iBin = 12; iBin < 24; iBin++) {
	                tempchordvalue += chorddict[24 * iChord + iBin] * chroma[iBin];
	            }
	            sumchordvalue+=tempchordvalue;
	            currentChordSalience.push_back(tempchordvalue);
	        }
	        for (int iChord = 0; iChord < nChord; iChord++) {
	            currentChordSalience[iChord] /= sumchordvalue;
	        }
	        chordogram.push_back(currentChordSalience);
	        
	        fsOut[3].push_back(f3);
	        fsOut[4].push_back(f4);
	        fsOut[5].push_back(f5);
	        fsOut[6].push_back(f6);
	        count++;
	    }
	//     int musicitykernelwidth = (50 * 2048) / m_stepSize;
	//     
	    /* Simple chord estimation
	    I just take the local chord estimates ("currentChordSalience") and average them over time, then
	    take the maximum. Very simple, don't do this at home...
	    */
	    count = 0; 
	    int halfwindowlength = m_inputSampleRate / m_stepSize;
	    int nChord = nChorddict / 24;
	    vector<int> chordSequence;
  	 	for (FeatureList::iterator it = fsOut[6].begin(); it != fsOut[6].end(); ++it) { // initialise the score chordogram
			vector<int> temp = vector<int>(nChord,0);
			scoreChordogram.push_back(temp);
		}
	    for (FeatureList::iterator it = fsOut[6].begin(); it < fsOut[6].end()-2*halfwindowlength-1; ++it) {		
			int startIndex = count + 1;
			int endIndex = count + 2 * halfwindowlength;
	        vector<float> temp = vector<float>(nChord,0);
			float maxval = 0; // will be the value of the most salient chord in this frame
			float maxindex = 0; //... and the index thereof
			unsigned bestchordL = 0; // index of the best "left" chord
 	 		unsigned bestchordR = 0; // index of the best "right" chord
			for (int iWF = 1; iWF < 2*halfwindowlength; ++iWF) {
				// now find the max values on both sides of iWF
				// left side:
				float maxL = 0;
				unsigned maxindL = nChord-1;
				for (unsigned iChord = 0; iChord < nChord; iChord++) {
					float currsum = 0;
					for (unsigned iFrame = 0; iFrame < iWF-1; ++iFrame) {
						currsum += chordogram[count+iFrame][iChord];
					}
					if (iChord == nChord-1) currsum *= 0.8;
					if (currsum > maxL) {
						maxL = currsum;
						maxindL = iChord;
					}
				}				
				// right side:
				float maxR = 0;
				unsigned maxindR = nChord-1;
				for (unsigned iChord = 0; iChord < nChord; iChord++) {
					float currsum = 0;
					for (unsigned iFrame = iWF-1; iFrame < 2*halfwindowlength; ++iFrame) {
						currsum += chordogram[count+iFrame][iChord];
					}
					if (iChord == nChord-1) currsum *= 0.8;
					if (currsum > maxR) {
						maxR = currsum;
						maxindR = iChord;
					}
				}
				if (maxL+maxR > maxval) {					
					maxval = maxL+maxR;
					maxindex = iWF;
					bestchordL = maxindL;
					bestchordR = maxindR;
				}
				
			}
			// cerr << "maxindex: " << maxindex << ", bestchordR is " << bestchordR << ", of frame " << count << endl;
			// add a score to every chord-frame-point that was part of a maximum 
			for (unsigned iFrame = 0; iFrame < maxindex-1; ++iFrame) {
				scoreChordogram[iFrame+count][bestchordL]++;
			}
			for (unsigned iFrame = maxindex-1; iFrame < 2*halfwindowlength; ++iFrame) {
				scoreChordogram[iFrame+count][bestchordR]++;
			}
			count++;	
	    }

		count = 0;
	 	for (FeatureList::iterator it = fsOut[6].begin(); it != fsOut[6].end(); ++it) { 
			float maxval = 0; // will be the value of the most salient chord in this frame
			float maxindex = 0; //... and the index thereof
			for (unsigned iChord = 0; iChord < nChord; iChord++) {
				if (scoreChordogram[count][iChord] > maxval) {
					maxval = scoreChordogram[count][iChord];
					maxindex = iChord;
					// cerr << iChord << endl;
				}
			}
			chordSequence.push_back(maxindex);
			// cerr << "before modefilter, maxindex: " << maxindex << endl;
			count++;
		}
	
	
	    // mode filter on chordSequence
	    count = 0;
	    int oldChordIndex = -1;
	    for (FeatureList::iterator it = fsOut[6].begin(); it != fsOut[6].end(); ++it) {
			Feature f6 = *it;
			Feature f7; // chord estimate
			f7.hasTimestamp = true;
			f7.timestamp = f6.timestamp;
			vector<int> chordCount = vector<int>(nChord,0);
	        int maxChordCount = 0;
	        int maxChordIndex = nChord-1;
	        int startIndex = max(count - halfwindowlength/2,0);
	        int endIndex = min(int(chordogram.size()), count + halfwindowlength/2);
	        for (int i = startIndex; i < endIndex; i++) {				
	            chordCount[chordSequence[i]]++;
	            if (chordCount[chordSequence[i]] > maxChordCount) {
					cerr << "start index " << startIndex << endl;
	                maxChordCount++;
	                maxChordIndex = chordSequence[i];
	            }
	        }
			// chordSequence[count] = maxChordIndex;
			cerr << maxChordIndex << endl;
	        if (oldChordIndex != maxChordIndex) {
	            oldChordIndex = maxChordIndex;
	
	            char buffer1 [50];
	            if (maxChordIndex < nChord - 1) {
	                sprintf(buffer1, "%s%s", notenames[maxChordIndex % 12 + 12], chordtypes[maxChordIndex]);
	            } else {
	                sprintf(buffer1, "N");
	            }
	            f7.label = buffer1;
	            fsOut[7].push_back(f7);
	        }
	        count++;
	    }
	//     // musicity
	//     count = 0;
	//     int oldlabeltype = 0; // start value is 0, music is 1, speech is 2
	//     vector<float> musicityValue; 
	//     for (FeatureList::iterator it = fsOut[4].begin(); it != fsOut[4].end(); ++it) {
	//         Feature f4 = *it;
	//         
	//         int startIndex = max(count - musicitykernelwidth/2,0);
	//         int endIndex = min(int(chordogram.size()), startIndex + musicitykernelwidth - 1);
	//         float chromasum = 0;
	//         float diffsum = 0;
	//         for (int k = 0; k < 12; k++) {
	//             for (int i = startIndex + 1; i < endIndex; i++) {
	//                 chromasum += pow(fsOut[4][i].values[k],2);
	//                 diffsum += abs(fsOut[4][i-1].values[k] - fsOut[4][i].values[k]);
	//             }
	//         }
	//         diffsum /= chromasum;
	//         musicityValue.push_back(diffsum);        
	//         count++;
	//     }
	//     
	//     float musicityThreshold = 0.44;
	//     if (m_stepSize == 4096) {
	//         musicityThreshold = 0.74;
	//     }
	//     if (m_stepSize == 4410) {
	//         musicityThreshold = 0.77;
	//     }
	//     
	//     count = 0;
	//     for (FeatureList::iterator it = fsOut[4].begin(); it != fsOut[4].end(); ++it) {
	//         Feature f4 = *it;
	//         Feature f8; // musicity
	//         Feature f9; // musicity segmenter
	//         
	//         f8.hasTimestamp = true;
	//         f8.timestamp = f4.timestamp;
	//         f9.hasTimestamp = true;
	//         f9.timestamp = f4.timestamp;    
	//         
	//         int startIndex = max(count - musicitykernelwidth/2,0);
	//         int endIndex = min(int(chordogram.size()), startIndex + musicitykernelwidth - 1);
	//         int musicityCount = 0;
	//         for (int i = startIndex; i <= endIndex; i++) {
	//             if (musicityValue[i] > musicityThreshold) musicityCount++;
	//         }
	//         bool isSpeech = (2 * musicityCount > endIndex - startIndex + 1); 
	//         
	//         if (isSpeech) {
	//             if (oldlabeltype != 2) {
	//                 f9.label = "Speech";
	//                 fsOut[9].push_back(f9);
	//                 oldlabeltype = 2;
	//             }
	//         } else {
	//             if (oldlabeltype != 1) {
	//                 f9.label = "Music";
	//                 fsOut[9].push_back(f9);
	//                 oldlabeltype = 1;
	//             }
	//         }
	//         f8.values.push_back(musicityValue[count]);
	//         fsOut[8].push_back(f8);
	//         count++;
	//      }
     return fsOut;     

}