annotate CepstralPitchTracker.cpp @ 66:7ad142c710c6 parameters

Add some parameters

/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
/*
    This file is Copyright (c) 2012 Chris Cannam
  
    Permission is hereby granted, free of charge, to any person
    obtaining a copy of this software and associated documentation
    files (the "Software"), to deal in the Software without
    restriction, including without limitation the rights to use, copy,
    modify, merge, publish, distribute, sublicense, and/or sell copies
    of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:

    The above copyright notice and this permission notice shall be
    included in all copies or substantial portions of the Software.

    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
    EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
    MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
    NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR
    ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
    CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
    WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*/

#include "CepstralPitchTracker.h"
#include "Cepstrum.h"
#include "MeanFilter.h"
#include "PeakInterpolator.h"
#include "AgentFeeder.h"

#include "vamp-sdk/FFT.h"

#include <vector>
#include <algorithm>

#include <cstdio>
#include <cmath>
#include <complex>

using std::string;
using std::vector;
using Vamp::RealTime;


CepstralPitchTracker::CepstralPitchTracker(float inputSampleRate) :
    Plugin(inputSampleRate),
    m_channels(0),
    m_stepSize(256),
    m_blockSize(1024),
    m_fmin(50),
    m_fmax(900),
    m_vflen(1),
    m_slack(40),
    m_sensitivity(10),
    m_threshold(0.1),
    m_binFrom(0),
    m_binTo(0),
    m_bins(0),
    m_nAccepted(0),
    m_feeder(0)
{
}

CepstralPitchTracker::~CepstralPitchTracker()
{
    delete m_feeder;
}

string
CepstralPitchTracker::getIdentifier() const
{
    return "cepstral-pitchtracker";
}

string
CepstralPitchTracker::getName() const
{
    return "Cepstral Pitch Tracker";
}

string
CepstralPitchTracker::getDescription() const
{
    return "Estimate f0 of monophonic material using a cepstrum method.";
}

string
CepstralPitchTracker::getMaker() const
{
    return "Chris Cannam";
}

int
CepstralPitchTracker::getPluginVersion() const
{
    // Increment this each time you release a version that behaves
    // differently from the previous one
    return 2;
}

string
CepstralPitchTracker::getCopyright() const
{
    return "Freely redistributable (BSD license)";
}

CepstralPitchTracker::InputDomain
CepstralPitchTracker::getInputDomain() const
{
    return FrequencyDomain;
}

size_t
CepstralPitchTracker::getPreferredBlockSize() const
{
    return 1024;
}

size_t 
CepstralPitchTracker::getPreferredStepSize() const
{
    return 256;
}

size_t
CepstralPitchTracker::getMinChannelCount() const
{
    return 1;
}

size_t
CepstralPitchTracker::getMaxChannelCount() const
{
    return 1;
}

CepstralPitchTracker::ParameterList
CepstralPitchTracker::getParameterDescriptors() const
{
    ParameterList list;

    ParameterDescriptor d;
    d.identifier = "sensitivity";
    d.name = "Sensitivity";
    d.description = "Sensitivity of the voicing detector";
    d.unit = "";
    d.minValue = 0;
    d.maxValue = 100;
    d.defaultValue = 10;
    d.isQuantized = true;
    d.quantizeStep = 1;
    list.push_back(d);

    d.identifier = "slack";
    d.name = "Slack";
    d.description = "Maximum permissible length of voicing gap for a continuous note";
    d.unit = "ms";
    d.minValue = 0;
    d.maxValue = 200;
    d.defaultValue = 40;
    d.isQuantized = true;
    d.quantizeStep = 1;
    list.push_back(d);
    
    d.identifier = "threshold";
    d.name = "Silence threshold";
    d.description = "Threshold for silence detection";
    d.unit = ""; //!!! todo: convert this threshold to a meaningful unit!
    d.minValue = 0;
    d.maxValue = 0.5;
    d.defaultValue = 0.1;
    d.isQuantized = false;
    list.push_back(d);
    
    return list;
}

float
CepstralPitchTracker::getParameter(string identifier) const
{
    if (identifier == "sensitivity") return m_sensitivity;
    else if (identifier == "slack") return m_slack;
    else if (identifier == "threshold") return m_threshold;
    return 0.f;
}

void
CepstralPitchTracker::setParameter(string identifier, float value) 
{
    if (identifier == "sensitivity") m_sensitivity = value;
    else if (identifier == "slack") m_slack = value;
    else if (identifier == "threshold") m_threshold = value;
}

CepstralPitchTracker::ProgramList
CepstralPitchTracker::getPrograms() const
{
    ProgramList list;
    return list;
}

string
CepstralPitchTracker::getCurrentProgram() const
{
    return ""; // no programs
}

void
CepstralPitchTracker::selectProgram(string name)
{
}

CepstralPitchTracker::OutputList
CepstralPitchTracker::getOutputDescriptors() const
{
    OutputList outputs;

    OutputDescriptor d;

    d.identifier = "f0";
    d.name = "Estimated f0";
    d.description = "Estimated fundamental frequency";
    d.unit = "Hz";
    d.hasFixedBinCount = true;
    d.binCount = 1;
    d.hasKnownExtents = true;
    d.minValue = m_fmin;
    d.maxValue = m_fmax;
    d.isQuantized = false;
    d.sampleType = OutputDescriptor::FixedSampleRate;
    d.sampleRate = (m_inputSampleRate / m_stepSize);
    d.hasDuration = false;
    outputs.push_back(d);

    d.identifier = "notes";
    d.name = "Notes";
    d.description = "Derived fixed-pitch note frequencies";
    d.unit = "Hz";
    d.hasFixedBinCount = true;
    d.binCount = 1;
    d.hasKnownExtents = true;
    d.minValue = m_fmin;
    d.maxValue = m_fmax;
    d.isQuantized = false;
    d.sampleType = OutputDescriptor::FixedSampleRate;
    d.sampleRate = (m_inputSampleRate / m_stepSize);
    d.hasDuration = true;
    outputs.push_back(d);

    d.identifier = "raw";
    d.name = "Raw frequencies";
    d.description = "Raw peak frequencies from cepstrum, including unvoiced segments";
    d.unit = "Hz";
    d.hasFixedBinCount = true;
    d.binCount = 1;
    d.hasKnownExtents = true;
    d.minValue = m_fmin;
    d.maxValue = m_fmax;
    d.isQuantized = false;
    d.sampleType = OutputDescriptor::OneSamplePerStep;
    d.hasDuration = false;
    outputs.push_back(d);

    return outputs;
}

bool
CepstralPitchTracker::initialise(size_t channels, size_t stepSize, size_t blockSize)
{
    if (channels < getMinChannelCount() ||
	channels > getMaxChannelCount()) return false;

//    std::cerr << "CepstralPitchTracker::initialise: channels = " << channels
//	      << ", stepSize = " << stepSize << ", blockSize = " << blockSize
//	      << std::endl;

    m_channels = channels;
    m_stepSize = stepSize;
    m_blockSize = blockSize;

    m_binFrom = int(m_inputSampleRate / m_fmax);
    m_binTo = int(m_inputSampleRate / m_fmin); 

    if (m_binTo >= (int)m_blockSize / 2) {
        m_binTo = m_blockSize / 2 - 1;
    }
    if (m_binFrom >= m_binTo) {
        // shouldn't happen except for degenerate samplerate / blocksize combos
        m_binFrom = m_binTo - 1;
    }

    m_bins = (m_binTo - m_binFrom) + 1;

    reset();

    return true;
}

void
CepstralPitchTracker::reset()
{
    delete m_feeder;
    m_feeder = new AgentFeeder(m_slack);
    m_nAccepted = 0;
}

void
CepstralPitchTracker::addFeaturesFrom(NoteHypothesis h, FeatureSet &fs)
{
    NoteHypothesis::Estimates es = h.getAcceptedEstimates();

    for (int i = 0; i < (int)es.size(); ++i) {
	Feature f;
	f.hasTimestamp = true;
	f.timestamp = es[i].time;
	f.values.push_back(es[i].freq);
	fs[0].push_back(f);
    }

    Feature nf;
    nf.hasTimestamp = true;
    nf.hasDuration = true;
    NoteHypothesis::Note n = h.getAveragedNote();
    nf.timestamp = n.time;
    nf.duration = n.duration;
    nf.values.push_back(n.freq);
    fs[1].push_back(nf);
}

void
CepstralPitchTracker::addNewFeatures(FeatureSet &fs)
{
    int n = m_feeder->getAcceptedHypotheses().size();
    if (n == m_nAccepted) return;

    AgentFeeder::Hypotheses accepted = m_feeder->getAcceptedHypotheses();

    for (int i = m_nAccepted; i < n; ++i) {
        addFeaturesFrom(accepted[i], fs);
    }

    m_nAccepted = n;
}

CepstralPitchTracker::FeatureSet
CepstralPitchTracker::process(const float *const *inputBuffers, RealTime timestamp)
{
    double *rawcep = new double[m_blockSize];
    double magmean = Cepstrum(m_blockSize).process(inputBuffers[0], rawcep);

    int n = m_bins;
    double *data = new double[n];
    MeanFilter(m_vflen).filterSubsequence
        (rawcep, data, m_blockSize, n, m_binFrom);

    delete[] rawcep;

    double maxval = 0.0;
    int maxbin = -1;

    for (int i = 0; i < n; ++i) {
        if (data[i] > maxval) {
            maxval = data[i];
            maxbin = i;
        }
    }

    if (maxbin < 0) {
        delete[] data;
        return FeatureSet();
    }

    double nextPeakVal = 0.0;
    for (int i = 1; i+1 < n; ++i) {
        if (data[i] > data[i-1] &&
            data[i] > data[i+1] &&
            i != maxbin &&
            data[i] > nextPeakVal) {
            nextPeakVal = data[i];
        }
    }

    PeakInterpolator pi;
    double cimax = pi.findPeakLocation(data, m_bins, maxbin);
    double peakfreq = m_inputSampleRate / (cimax + m_binFrom);

    FeatureSet fs;
    Feature rawf;
    rawf.hasTimestamp = false;
    rawf.hasDuration = false;
    rawf.values.push_back(peakfreq);
    fs[2].push_back(rawf);

    double confidence = 0.0;

    if (nextPeakVal != 0.0) {
        confidence = (maxval - nextPeakVal) * m_sensitivity;
        if (magmean < m_threshold) confidence = 0.0;
    }

    delete[] data;

    NoteHypothesis::Estimate e;
    e.freq = peakfreq;
    e.time = timestamp;
    e.confidence = confidence;

    m_feeder->feed(e);

    addNewFeatures(fs);
    return fs;
}

CepstralPitchTracker::FeatureSet
CepstralPitchTracker::getRemainingFeatures()
{
    m_feeder->finish();

    FeatureSet fs;
    addNewFeatures(fs);
    return fs;
}