annotate MonoNoteHMM.cpp @ 164:a7d9c6142f8f tip

Added tag v1.2 for changeset 4a97f7638ffd
author Chris Cannam
date Thu, 06 Feb 2020 15:02:47 +0000
parents 3faac48d491d
children
rev   line source
Chris@9 1 /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */
Chris@9 2
Chris@9 3 /*
Chris@9 4 pYIN - A fundamental frequency estimator for monophonic audio
Chris@9 5 Centre for Digital Music, Queen Mary, University of London.
Chris@9 6
Chris@9 7 This program is free software; you can redistribute it and/or
Chris@9 8 modify it under the terms of the GNU General Public License as
Chris@9 9 published by the Free Software Foundation; either version 2 of the
Chris@9 10 License, or (at your option) any later version. See the file
Chris@9 11 COPYING included with this distribution for more information.
Chris@9 12 */
Chris@9 13
matthiasm@0 14 #include "MonoNoteHMM.h"
matthiasm@0 15
matthiasm@0 16 #include <boost/math/distributions.hpp>
matthiasm@0 17
matthiasm@0 18 #include <cstdio>
matthiasm@0 19 #include <cmath>
matthiasm@0 20
matthiasm@0 21 using std::vector;
matthiasm@0 22 using std::pair;
matthiasm@0 23
mail@132 24 MonoNoteHMM::MonoNoteHMM(int fixedLag) :
mail@132 25 SparseHMM(fixedLag),
matthiasm@0 26 par()
matthiasm@0 27 {
matthiasm@0 28 build();
matthiasm@0 29 }
matthiasm@0 30
Chris@145 31 vector<double>
Chris@156 32 MonoNoteHMM::calculateObsProb(const vector<pair<double, double> > &pitchProb)
matthiasm@0 33 {
matthiasm@0 34 // pitchProb is a list of pairs (pitches and their probabilities)
matthiasm@0 35
matthiasm@0 36 size_t nCandidate = pitchProb.size();
matthiasm@0 37
matthiasm@0 38 // what is the probability of pitched
matthiasm@0 39 double pIsPitched = 0;
mail@133 40 for (size_t iCand = 0; iCand < nCandidate; ++iCand)
matthiasm@0 41 {
mail@133 42 pIsPitched += pitchProb[iCand].second;
matthiasm@0 43 }
matthiasm@0 44
mail@133 45 pIsPitched = pIsPitched * (1-par.priorWeight) +
mail@133 46 par.priorPitchedProb * par.priorWeight;
matthiasm@0 47
matthiasm@0 48 vector<double> out = vector<double>(par.n);
matthiasm@0 49 double tempProbSum = 0;
matthiasm@0 50 for (size_t i = 0; i < par.n; ++i)
matthiasm@0 51 {
matthiasm@103 52 if (i % par.nSPP != 2)
matthiasm@0 53 {
matthiasm@0 54 // std::cerr << getMidiPitch(i) << std::endl;
matthiasm@0 55 double tempProb = 0;
matthiasm@0 56 if (nCandidate > 0)
matthiasm@0 57 {
matthiasm@0 58 double minDist = 10000.0;
matthiasm@0 59 double minDistProb = 0;
matthiasm@0 60 size_t minDistCandidate = 0;
mail@133 61 for (size_t iCand = 0; iCand < nCandidate; ++iCand)
matthiasm@0 62 {
mail@133 63 double currDist = std::abs(getMidiPitch(i)-
mail@133 64 pitchProb[iCand].first);
matthiasm@0 65 if (currDist < minDist)
matthiasm@0 66 {
matthiasm@0 67 minDist = currDist;
mail@133 68 minDistProb = pitchProb[iCand].second;
mail@133 69 minDistCandidate = iCand;
matthiasm@0 70 }
matthiasm@0 71 }
matthiasm@101 72 tempProb = std::pow(minDistProb, par.yinTrust) *
matthiasm@101 73 boost::math::pdf(pitchDistr[i],
matthiasm@101 74 pitchProb[minDistCandidate].first);
matthiasm@0 75 } else {
matthiasm@0 76 tempProb = 1;
matthiasm@0 77 }
matthiasm@0 78 tempProbSum += tempProb;
matthiasm@0 79 out[i] = tempProb;
matthiasm@0 80 }
matthiasm@0 81 }
matthiasm@0 82
matthiasm@0 83 for (size_t i = 0; i < par.n; ++i)
matthiasm@0 84 {
matthiasm@103 85 if (i % par.nSPP != 2)
matthiasm@0 86 {
matthiasm@0 87 if (tempProbSum > 0)
matthiasm@0 88 {
matthiasm@0 89 out[i] = out[i] / tempProbSum * pIsPitched;
matthiasm@0 90 }
matthiasm@0 91 } else {
matthiasm@0 92 out[i] = (1-pIsPitched) / (par.nPPS * par.nS);
matthiasm@0 93 }
matthiasm@0 94 }
Chris@146 95
matthiasm@0 96 return(out);
matthiasm@0 97 }
matthiasm@0 98
matthiasm@0 99 void
matthiasm@0 100 MonoNoteHMM::build()
matthiasm@0 101 {
matthiasm@0 102 // the states are organised as follows:
matthiasm@0 103 // 0-2. lowest pitch
matthiasm@0 104 // 0. attack state
matthiasm@0 105 // 1. stable state
matthiasm@0 106 // 2. silent state
matthiasm@103 107 // 3-5. second-lowest pitch
matthiasm@103 108 // 3. attack state
matthiasm@0 109 // ...
matthiasm@0 110
mail@130 111 m_nState = par.n;
mail@130 112
matthiasm@0 113 // observation distributions
matthiasm@0 114 for (size_t iState = 0; iState < par.n; ++iState)
matthiasm@0 115 {
matthiasm@0 116 pitchDistr.push_back(boost::math::normal(0,1));
matthiasm@103 117 if (iState % par.nSPP == 2)
matthiasm@0 118 {
matthiasm@0 119 // silent state starts tracking
mail@130 120 m_init.push_back(1.0/(par.nS * par.nPPS));
matthiasm@0 121 } else {
mail@130 122 m_init.push_back(0.0);
matthiasm@0 123 }
matthiasm@0 124 }
matthiasm@0 125
matthiasm@0 126 for (size_t iPitch = 0; iPitch < (par.nS * par.nPPS); ++iPitch)
matthiasm@0 127 {
matthiasm@0 128 size_t index = iPitch * par.nSPP;
matthiasm@0 129 double mu = par.minPitch + iPitch * 1.0/par.nPPS;
matthiasm@0 130 pitchDistr[index] = boost::math::normal(mu, par.sigmaYinPitchAttack);
matthiasm@0 131 pitchDistr[index+1] = boost::math::normal(mu, par.sigmaYinPitchStable);
matthiasm@0 132 pitchDistr[index+2] = boost::math::normal(mu, 1.0); // dummy
matthiasm@0 133 }
matthiasm@0 134
matthiasm@0 135 boost::math::normal noteDistanceDistr(0, par.sigma2Note);
matthiasm@0 136
matthiasm@0 137 for (size_t iPitch = 0; iPitch < (par.nS * par.nPPS); ++iPitch)
matthiasm@0 138 {
matthiasm@0 139 // loop through all notes and set sparse transition probabilities
matthiasm@0 140 size_t index = iPitch * par.nSPP;
matthiasm@0 141
matthiasm@0 142 // transitions from attack state
mail@130 143 m_from.push_back(index);
mail@130 144 m_to.push_back(index);
mail@130 145 m_transProb.push_back(par.pAttackSelftrans);
matthiasm@0 146
mail@130 147 m_from.push_back(index);
mail@130 148 m_to.push_back(index+1);
mail@130 149 m_transProb.push_back(1-par.pAttackSelftrans);
matthiasm@0 150
matthiasm@0 151 // transitions from stable state
mail@130 152 m_from.push_back(index+1);
mail@130 153 m_to.push_back(index+1); // to itself
mail@130 154 m_transProb.push_back(par.pStableSelftrans);
matthiasm@0 155
mail@130 156 m_from.push_back(index+1);
mail@130 157 m_to.push_back(index+2); // to silent
mail@130 158 m_transProb.push_back(par.pStable2Silent);
matthiasm@0 159
matthiasm@0 160 // the "easy" transitions from silent state
mail@130 161 m_from.push_back(index+2);
mail@130 162 m_to.push_back(index+2);
mail@130 163 m_transProb.push_back(par.pSilentSelftrans);
matthiasm@0 164
matthiasm@0 165
matthiasm@106 166 // the more complicated transitions from the silent
matthiasm@0 167 double probSumSilent = 0;
matthiasm@106 168
matthiasm@0 169 vector<double> tempTransProbSilent;
matthiasm@0 170 for (size_t jPitch = 0; jPitch < (par.nS * par.nPPS); ++jPitch)
matthiasm@0 171 {
matthiasm@0 172 int fromPitch = iPitch;
matthiasm@0 173 int toPitch = jPitch;
matthiasm@101 174 double semitoneDistance =
matthiasm@101 175 std::abs(fromPitch - toPitch) * 1.0 / par.nPPS;
matthiasm@0 176
mail@133 177
matthiasm@101 178 if (semitoneDistance == 0 ||
matthiasm@101 179 (semitoneDistance > par.minSemitoneDistance
matthiasm@101 180 && semitoneDistance < par.maxJump))
matthiasm@0 181 {
matthiasm@0 182 size_t toIndex = jPitch * par.nSPP; // note attack index
matthiasm@0 183
matthiasm@101 184 double tempWeightSilent = boost::math::pdf(noteDistanceDistr,
matthiasm@101 185 semitoneDistance);
matthiasm@0 186 probSumSilent += tempWeightSilent;
matthiasm@0 187
matthiasm@0 188 tempTransProbSilent.push_back(tempWeightSilent);
matthiasm@0 189
mail@130 190 m_from.push_back(index+2);
mail@130 191 m_to.push_back(toIndex);
matthiasm@0 192 }
matthiasm@0 193 }
matthiasm@0 194 for (size_t i = 0; i < tempTransProbSilent.size(); ++i)
matthiasm@0 195 {
mail@133 196 m_transProb.push_back((1-par.pSilentSelftrans) *
mail@133 197 tempTransProbSilent[i]/probSumSilent);
matthiasm@0 198 }
matthiasm@0 199 }
mail@130 200 m_nTrans = m_transProb.size();
mail@130 201 m_delta = vector<double>(m_nState);
mail@130 202 m_oldDelta = vector<double>(m_nState);
matthiasm@0 203 }
matthiasm@0 204
matthiasm@0 205 double
matthiasm@0 206 MonoNoteHMM::getMidiPitch(size_t index)
matthiasm@0 207 {
matthiasm@0 208 return pitchDistr[index].mean();
matthiasm@0 209 }
matthiasm@0 210
matthiasm@0 211 double
matthiasm@0 212 MonoNoteHMM::getFrequency(size_t index)
matthiasm@0 213 {
matthiasm@0 214 return 440 * pow(2, (pitchDistr[index].mean()-69)/12);
matthiasm@0 215 }