autoSpectrum Spectrum_compressFrequencyDomain (Spectrum me, double fmax, long interpolationDepth, int freqscale, int method) {
try {
double fdomain = my xmax - my xmin, factor = fdomain / fmax ;
//long numberOfFrequencies = 1.0 + fmax / my dx; // keep dx the same, otherwise the "duration" changes
double xmax = my xmax / factor;
long numberOfFrequencies = (long) floor (my nx / factor); // keep dx the same, otherwise the "duration" changes
autoSpectrum thee = Spectrum_create (xmax, numberOfFrequencies);
thy z[1][1] = my z[1][1]; thy z[2][1] = my z[2][1];
double df = freqscale == 1 ? factor * my dx : log10 (fdomain) / (numberOfFrequencies - 1);
for (long i = 2; i <= numberOfFrequencies; i++) {
double f = my xmin + (freqscale == 1 ? (i - 1) * df : pow (10.0, (i - 1) * df));
double x, y, index = (f - my x1) / my dx + 1;
if (index > my nx) {
break;
}
if (method == 1) {
x = NUM_interpolate_sinc (my z[1], my nx, index, interpolationDepth);
y = NUM_interpolate_sinc (my z[2], my nx, index, interpolationDepth);
} else {
x = NUMundefined; // ppgb: better than data from random memory
y = NUMundefined;
}
thy z[1][i] = x; thy z[2][i] = y;
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": not compressed.");
}
}
autoSpectrum Spectrum_shiftFrequencies (Spectrum me, double shiftBy, double newMaximumFrequency, long interpolationDepth) {
try {
double xmax = my xmax;
long numberOfFrequencies = my nx;
if (newMaximumFrequency != 0) {
numberOfFrequencies = (long) floor (newMaximumFrequency / my dx) + 1;
xmax = newMaximumFrequency;
}
autoSpectrum thee = Spectrum_create (xmax, numberOfFrequencies);
// shiftBy >= 0
for (long i = 1; i <= thy nx; i++) {
double thyf = thy x1 + (i - 1) * thy dx;
double myf = thyf - shiftBy;
if (myf >= my xmin && myf <= my xmax) {
double index = Sampled_xToIndex (me, myf);
thy z[1][i] = NUM_interpolate_sinc (my z[1], my nx, index, interpolationDepth);
thy z[2][i] = NUM_interpolate_sinc (my z[2], my nx, index, interpolationDepth);
}
}
// Make imaginary part of first and last sample zero
// so Spectrum_to_Sound uses FFT if numberOfSamples was power of 2!
double amp = sqrt (thy z[1][1] * thy z[1][1] + thy z[2][1] * thy z[2][1]);
thy z[1][1] = amp; thy z[2][1] = 0;
amp = sqrt (thy z[1][thy nx] * thy z[1][thy nx] + thy z[2][thy nx] * thy z[2][thy nx]);
thy z[1][thy nx] = amp; thy z[2][thy nx] = 0;
return thee;
} catch (MelderError) {
Melder_throw (me, U": not shifted.");
}
}
Sound Sound_resample (Sound me, double samplingFrequency, long precision) {
double upfactor = samplingFrequency * my dx;
if (fabs (upfactor - 2) < 1e-6) return Sound_upsample (me);
if (fabs (upfactor - 1) < 1e-6) return Data_copy (me);
try {
long numberOfSamples = lround ((my xmax - my xmin) * samplingFrequency);
if (numberOfSamples < 1)
Melder_throw (U"The resampled Sound would have no samples.");
autoSound filtered = NULL;
if (upfactor < 1.0) { // need anti-aliasing filter?
long nfft = 1, antiTurnAround = 1000;
while (nfft < my nx + antiTurnAround * 2) nfft *= 2;
autoNUMvector <double> data (1, nfft);
filtered.reset (Sound_create (my ny, my xmin, my xmax, my nx, my dx, my x1));
for (long channel = 1; channel <= my ny; channel ++) {
for (long i = 1; i <= nfft; i ++) {
data [i] = 0;
}
NUMvector_copyElements (my z [channel], & data [antiTurnAround], 1, my nx);
NUMrealft (data.peek(), nfft, 1); // go to the frequency domain
for (long i = (long) floor (upfactor * nfft); i <= nfft; i ++) {
data [i] = 0; // filter away high frequencies
}
data [2] = 0.0;
NUMrealft (data.peek(), nfft, -1); // return to the time domain
double factor = 1.0 / nfft;
double *to = filtered -> z [channel];
for (long i = 1; i <= my nx; i ++) {
to [i] = data [i + antiTurnAround] * factor;
}
}
me = filtered.peek(); // reference copy; remove at end
}
autoSound thee = Sound_create (my ny, my xmin, my xmax, numberOfSamples, 1.0 / samplingFrequency,
0.5 * (my xmin + my xmax - (numberOfSamples - 1) / samplingFrequency));
for (long channel = 1; channel <= my ny; channel ++) {
double *from = my z [channel];
double *to = thy z [channel];
if (precision <= 1) {
for (long i = 1; i <= numberOfSamples; i ++) {
double x = Sampled_indexToX (thee.peek(), i);
double index = Sampled_xToIndex (me, x);
long leftSample = (long) floor (index);
double fraction = index - leftSample;
to [i] = leftSample < 1 || leftSample >= my nx ? 0.0 :
(1 - fraction) * from [leftSample] + fraction * from [leftSample + 1];
}
} else {
for (long i = 1; i <= numberOfSamples; i ++) {
double x = Sampled_indexToX (thee.peek(), i);
double index = Sampled_xToIndex (me, x);
to [i] = NUM_interpolate_sinc (my z [channel], my nx, index, precision);
}
}
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, U": not resampled.");
}
}
//
// Vector_getValueAtX () returns the average of all the interpolated channels.
//
double Vector_getValueAtX (Vector me, double x, long ilevel, int interpolation) {
double leftEdge = my x1 - 0.5 * my dx, rightEdge = leftEdge + my nx * my dx;
if (x < leftEdge || x > rightEdge) return NUMundefined;
if (ilevel > Vector_CHANNEL_AVERAGE) {
Melder_assert (ilevel <= my ny);
return NUM_interpolate_sinc (my z [ilevel], my nx, Sampled_xToIndex (me, x),
interpolation == Vector_VALUE_INTERPOLATION_SINC70 ? NUM_VALUE_INTERPOLATE_SINC70 :
interpolation == Vector_VALUE_INTERPOLATION_SINC700 ? NUM_VALUE_INTERPOLATE_SINC700 :
interpolation);
}
double sum = 0.0;
for (long channel = 1; channel <= my ny; channel ++) {
sum += NUM_interpolate_sinc (my z [channel], my nx, Sampled_xToIndex (me, x),
interpolation == Vector_VALUE_INTERPOLATION_SINC70 ? NUM_VALUE_INTERPOLATE_SINC70 :
interpolation == Vector_VALUE_INTERPOLATION_SINC700 ? NUM_VALUE_INTERPOLATE_SINC700 :
interpolation);
}
return sum / my ny;
}
void ParamCurve_draw (ParamCurve me, Graphics g, double t1, double t2, double dt,
double x1, double x2, double y1, double y2, int garnish)
{
if (t2 <= t1) {
double tx1 = my x -> x1;
double ty1 = my y -> x1;
double tx2 = my x -> x1 + (my x -> nx - 1) * my x -> dx;
double ty2 = my y -> x1 + (my y -> nx - 1) * my y -> dx;
t1 = tx1 > ty1 ? tx1 : ty1;
t2 = tx2 < ty2 ? tx2 : ty2;
}
if (x2 <= x1) Matrix_getWindowExtrema (my x, 0, 0, 1, 1, & x1, & x2);
if (x1 == x2) { x1 -= 1.0; x2 += 1.0; }
if (y2 <= y1) Matrix_getWindowExtrema (my y, 0, 0, 1, 1, & y1, & y2);
if (y1 == y2) { y1 -= 1.0; y2 += 1.0; }
if (dt <= 0.0)
dt = my x -> dx < my y -> dx ? my x -> dx : my y -> dx;
long numberOfPoints = (long) ceil ((t2 - t1) / dt) + 1;
if (numberOfPoints > 0) {
autoNUMvector <double> x (1, numberOfPoints);
autoNUMvector <double> y (1, numberOfPoints);
for (long i = 1; i <= numberOfPoints; i ++) {
double t = i == numberOfPoints ? t2 : t1 + (i - 1) * dt;
double index = my x -> f_xToIndex (t);
x [i] = NUM_interpolate_sinc (my x -> z [1], my x -> nx, index, 50);
index = my y -> f_xToIndex (t);
y [i] = NUM_interpolate_sinc (my y -> z [1], my y -> nx, index, 50);
}
Graphics_setWindow (g, x1, x2, y1, y2);
Graphics_setInner (g);
Graphics_polyline (g, numberOfPoints, & x [1], & y [1]);
Graphics_unsetInner (g);
}
if (garnish) {
Graphics_drawInnerBox (g);
Graphics_marksBottom (g, 2, 1, 1, 0);
Graphics_marksLeft (g, 2, 1, 1, 0);
}
}
static autoSpectrum Spectrum_shiftFrequencies2 (Spectrum me, double shiftBy, bool changeMaximumFrequency) {
try {
double xmax = my xmax;
long numberOfFrequencies = my nx, interpolationDepth = 50;
if (changeMaximumFrequency) {
xmax += shiftBy;
numberOfFrequencies += (xmax - my xmax) / my dx;
}
autoSpectrum thee = Spectrum_create (xmax, numberOfFrequencies);
// shiftBy >= 0
for (long i = 1; i <= thy nx; i++) {
double thyf = thy x1 + (i - 1) * thy dx;
double myf = thyf - shiftBy;
if (myf >= my xmin && myf <= my xmax) {
double index = Sampled_xToIndex (me, myf);
thy z[1][i] = NUM_interpolate_sinc (my z[1], my nx, index, interpolationDepth);
thy z[2][i] = NUM_interpolate_sinc (my z[2], my nx, index, interpolationDepth);
}
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": not shifted.");
}
}
static void Sound_into_PitchFrame (Sound me, Pitch_Frame pitchFrame, double t,
double minimumPitch, int maxnCandidates, int method, double voicingThreshold, double octaveCost,
NUMfft_Table fftTable, double dt_window, long nsamp_window, long halfnsamp_window,
long maximumLag, long nsampFFT, long nsamp_period, long halfnsamp_period,
long brent_ixmax, long brent_depth, double globalPeak,
double **frame, double *ac, double *window, double *windowR,
double *r, long *imax, double *localMean)
{
double localPeak;
long leftSample = Sampled_xToLowIndex (me, t), rightSample = leftSample + 1;
long startSample, endSample;
for (long channel = 1; channel <= my ny; channel ++) {
/*
* Compute the local mean; look one longest period to both sides.
*/
startSample = rightSample - nsamp_period;
endSample = leftSample + nsamp_period;
Melder_assert (startSample >= 1);
Melder_assert (endSample <= my nx);
localMean [channel] = 0.0;
for (long i = startSample; i <= endSample; i ++) {
localMean [channel] += my z [channel] [i];
}
localMean [channel] /= 2 * nsamp_period;
/*
* Copy a window to a frame and subtract the local mean.
* We are going to kill the DC component before windowing.
*/
startSample = rightSample - halfnsamp_window;
endSample = leftSample + halfnsamp_window;
Melder_assert (startSample >= 1);
Melder_assert (endSample <= my nx);
if (method < FCC_NORMAL) {
for (long j = 1, i = startSample; j <= nsamp_window; j ++)
frame [channel] [j] = (my z [channel] [i ++] - localMean [channel]) * window [j];
for (long j = nsamp_window + 1; j <= nsampFFT; j ++)
frame [channel] [j] = 0.0;
} else {
for (long j = 1, i = startSample; j <= nsamp_window; j ++)
frame [channel] [j] = my z [channel] [i ++] - localMean [channel];
}
}
/*
* Compute the local peak; look half a longest period to both sides.
*/
localPeak = 0.0;
if ((startSample = halfnsamp_window + 1 - halfnsamp_period) < 1) startSample = 1;
if ((endSample = halfnsamp_window + halfnsamp_period) > nsamp_window) endSample = nsamp_window;
for (long channel = 1; channel <= my ny; channel ++) {
for (long j = startSample; j <= endSample; j ++) {
double value = fabs (frame [channel] [j]);
if (value > localPeak) localPeak = value;
}
}
pitchFrame->intensity = localPeak > globalPeak ? 1.0 : localPeak / globalPeak;
/*
* Compute the correlation into the array 'r'.
*/
if (method >= FCC_NORMAL) {
double startTime = t - 0.5 * (1.0 / minimumPitch + dt_window);
long localSpan = maximumLag + nsamp_window, localMaximumLag, offset;
if ((startSample = Sampled_xToLowIndex (me, startTime)) < 1) startSample = 1;
if (localSpan > my nx + 1 - startSample) localSpan = my nx + 1 - startSample;
localMaximumLag = localSpan - nsamp_window;
offset = startSample - 1;
double sumx2 = 0; // sum of squares
for (long channel = 1; channel <= my ny; channel ++) {
double *amp = my z [channel] + offset;
for (long i = 1; i <= nsamp_window; i ++) {
double x = amp [i] - localMean [channel];
sumx2 += x * x;
}
}
double sumy2 = sumx2; // at zero lag, these are still equal
r [0] = 1.0;
for (long i = 1; i <= localMaximumLag; i ++) {
double product = 0.0;
for (long channel = 1; channel <= my ny; channel ++) {
double *amp = my z [channel] + offset;
double y0 = amp [i] - localMean [channel];
double yZ = amp [i + nsamp_window] - localMean [channel];
sumy2 += yZ * yZ - y0 * y0;
for (long j = 1; j <= nsamp_window; j ++) {
double x = amp [j] - localMean [channel];
double y = amp [i + j] - localMean [channel];
product += x * y;
}
}
r [- i] = r [i] = product / sqrt (sumx2 * sumy2);
}
} else {
/*
* The FFT of the autocorrelation is the power spectrum.
*/
for (long i = 1; i <= nsampFFT; i ++) {
ac [i] = 0.0;
}
for (long channel = 1; channel <= my ny; channel ++) {
NUMfft_forward (fftTable, frame [channel]); // complex spectrum
ac [1] += frame [channel] [1] * frame [channel] [1]; // DC component
for (long i = 2; i < nsampFFT; i += 2) {
ac [i] += frame [channel] [i] * frame [channel] [i] + frame [channel] [i+1] * frame [channel] [i+1]; // power spectrum
}
ac [nsampFFT] += frame [channel] [nsampFFT] * frame [channel] [nsampFFT]; // Nyquist frequency
}
NUMfft_backward (fftTable, ac); /* Autocorrelation. */
/*
* Normalize the autocorrelation to the value with zero lag,
* and divide it by the normalized autocorrelation of the window.
*/
r [0] = 1.0;
for (long i = 1; i <= brent_ixmax; i ++)
r [- i] = r [i] = ac [i + 1] / (ac [1] * windowR [i + 1]);
}
/*
* Register the first candidate, which is always present: voicelessness.
*/
pitchFrame->nCandidates = 1;
pitchFrame->candidate[1].frequency = 0.0; // voiceless: always present
pitchFrame->candidate[1].strength = 0.0;
/*
* Shortcut: absolute silence is always voiceless.
* We are done for this frame.
*/
if (localPeak == 0) return;
/*
* Find the strongest maxima of the correlation of this frame,
* and register them as candidates.
*/
imax [1] = 0;
for (long i = 2; i < maximumLag && i < brent_ixmax; i ++)
if (r [i] > 0.5 * voicingThreshold && // not too unvoiced?
r [i] > r [i-1] && r [i] >= r [i+1]) // maximum?
{
int place = 0;
/*
* Use parabolic interpolation for first estimate of frequency,
* and sin(x)/x interpolation to compute the strength of this frequency.
*/
double dr = 0.5 * (r [i+1] - r [i-1]), d2r = 2 * r [i] - r [i-1] - r [i+1];
double frequencyOfMaximum = 1 / my dx / (i + dr / d2r);
long offset = - brent_ixmax - 1;
double strengthOfMaximum = /* method & 1 ? */
NUM_interpolate_sinc (& r [offset], brent_ixmax - offset, 1 / my dx / frequencyOfMaximum - offset, 30)
/* : r [i] + 0.5 * dr * dr / d2r */;
/* High values due to short windows are to be reflected around 1. */
if (strengthOfMaximum > 1.0) strengthOfMaximum = 1.0 / strengthOfMaximum;
/*
* Find a place for this maximum.
*/
if (pitchFrame->nCandidates < maxnCandidates) { // is there still a free place?
place = ++ pitchFrame->nCandidates;
} else {
/* Try the place of the weakest candidate so far. */
double weakest = 2;
for (int iweak = 2; iweak <= maxnCandidates; iweak ++) {
/* High frequencies are to be favoured */
/* if we want to analyze a perfectly periodic signal correctly. */
double localStrength = pitchFrame->candidate[iweak].strength - octaveCost *
NUMlog2 (minimumPitch / pitchFrame->candidate[iweak].frequency);
if (localStrength < weakest) { weakest = localStrength; place = iweak; }
}
/* If this maximum is weaker than the weakest candidate so far, give it no place. */
if (strengthOfMaximum - octaveCost * NUMlog2 (minimumPitch / frequencyOfMaximum) <= weakest)
place = 0;
}
if (place) { // have we found a place for this candidate?
pitchFrame->candidate[place].frequency = frequencyOfMaximum;
pitchFrame->candidate[place].strength = strengthOfMaximum;
imax [place] = i;
}
}
/*
* Second pass: for extra precision, maximize sin(x)/x interpolation ('sinc').
*/
for (long i = 2; i <= pitchFrame->nCandidates; i ++) {
if (method != AC_HANNING || pitchFrame->candidate[i].frequency > 0.0 / my dx) {
double xmid, ymid;
long offset = - brent_ixmax - 1;
ymid = NUMimproveMaximum (& r [offset], brent_ixmax - offset, imax [i] - offset,
pitchFrame->candidate[i].frequency > 0.3 / my dx ? NUM_PEAK_INTERPOLATE_SINC700 : brent_depth, & xmid);
xmid += offset;
pitchFrame->candidate[i].frequency = 1.0 / my dx / xmid;
if (ymid > 1.0) ymid = 1.0 / ymid;
pitchFrame->candidate[i].strength = ymid;
}
}
}
Pitch Sound_to_Pitch_any (Sound me, double dt, /*timeStepStradygy related*/
double minimumPitch, /*Pitch settings realted*/
double periodsPerWindow, /*kTimeSoundAnalysisEditor_pitch_analysisMethod related*/
int maxnCandidates,
int method, /*method related*/
double silenceThreshold, double voicingThreshold, double octaveCost, double octaveJumpCost,
double voicedUnvoicedCost, double ceiling)
{
NUMfft_Table fftTable = NUMfft_Table_create();
double duration, t1;
double dt_window; /* Window length in seconds. */
long nsamp_window, halfnsamp_window; /* Number of samples per window. */
long nFrames, minimumLag, maximumLag;
long iframe, nsampFFT;
double interpolation_depth;
long nsamp_period, halfnsamp_period; /* Number of samples in longest period. */
long brent_ixmax, brent_depth;
double brent_accuracy; /* Obsolete. */
double globalPeak;
if (maxnCandidates < 2 || method < AC_HANNING && method > FCC_ACCURATE)
{
std::cout<<"Error: maxnCandidates: "<<maxnCandidates<<" method: "<<method<<"."<<std::endl;
std::cout<<"Sound_to_Pitch.cpp: Line 13. 69"<<std::endl;
return NULL;
}
if (maxnCandidates < ceiling / minimumPitch) maxnCandidates = ceiling / minimumPitch;
if (dt <= 0.0) dt = periodsPerWindow / minimumPitch / 4.0; /* e.g. 3 periods, 75 Hz: 10 milliseconds. */
switch (method) {
case AC_HANNING:
brent_depth = NUM_PEAK_INTERPOLATE_SINC70;
brent_accuracy = 1e-7;
interpolation_depth = 0.5;
break;
case AC_GAUSS:
periodsPerWindow *= 2; /* Because Gaussian window is twice as long. */
brent_depth = NUM_PEAK_INTERPOLATE_SINC700;
brent_accuracy = 1e-11;
interpolation_depth = 0.25; /* Because Gaussian window is twice as long. */
break;
case FCC_NORMAL:
brent_depth = NUM_PEAK_INTERPOLATE_SINC70;
brent_accuracy = 1e-7;
interpolation_depth = 1.0;
break;
case FCC_ACCURATE:
brent_depth = NUM_PEAK_INTERPOLATE_SINC700;
brent_accuracy = 1e-11;
interpolation_depth = 1.0;
break;
}
duration = my dx * my nx;
if (minimumPitch < periodsPerWindow / duration) {
std::cout<<"To analyse this Sound, minimum pitch must not be less than "<< periodsPerWindow / duration<<" Hz."<<std::endl;
std::cout<<"Sound_to_Pitch.cpp: Line 31.103"<<std::endl;
return NULL;
}
/*
* Determine the number of samples in the longest period.
* We need this to compute the local mean of the sound (looking one period in both directions),
* and to compute the local peak of the sound (looking half a period in both directions).
*/
nsamp_period = floor(1 / my dx / minimumPitch);
halfnsamp_period = nsamp_period / 2 + 1;
if (ceiling > 0.5 / my dx) ceiling = 0.5 / my dx;
// Determine window length in seconds and in samples.
dt_window = periodsPerWindow / minimumPitch;
nsamp_window = floor (dt_window / my dx);
halfnsamp_window = nsamp_window / 2 - 1;
if (halfnsamp_window < 2){
std::cout<<"Analysis window too short."<<std::endl;
std::cout<<"Sound_to_Pitch.cpp: Line 31.123"<<std::endl;
return NULL;
}
nsamp_window = halfnsamp_window * 2;
// Determine the minimum and maximum lags.
minimumLag = floor (1 / my dx / ceiling);
if (minimumLag < 2) minimumLag = 2;
maximumLag = floor (nsamp_window / periodsPerWindow) + 2;
if (maximumLag > nsamp_window) maximumLag = nsamp_window;
/*
* Determine the number of frames.
* Fit as many frames as possible symmetrically in the total duration.
* We do this even for the forward cross-correlation method,
* because that allows us to compare the two methods.
*/
if(!Sampled_shortTermAnalysis (me, method >= FCC_NORMAL ? 1 / minimumPitch + dt_window : dt_window, dt, & nFrames, & t1)){
std::cout<<"The pitch analysis would give zero pitch frames."<<std::endl;
std::cout<<"Sound_to_Pitch.cpp: Line 31.142"<<std::endl;
return NULL;
}
// Create the resulting pitch contour.
Pitch thee = Pitch_create (my xmin, my xmax, nFrames, dt, t1, ceiling, maxnCandidates);
// Compute the global absolute peak for determination of silence threshold.
globalPeak = 0.0;
for (long channel = 1; channel <= my ny; channel ++) {
double mean = 0.0;
for (long i = 1; i <= my nx; i ++) {
mean += my z [channel] [i];
}
mean /= my nx;
for (long i = 1; i <= my nx; i ++) {
double value = fabs (my z [channel] [i] - mean);
if (value > globalPeak) globalPeak = value;
}
}
if (globalPeak == 0.0) return thee;
double **frame, *ac, *window, *windowR;
if (method >= FCC_NORMAL) { /* For cross-correlation analysis. */
// Create buffer for cross-correlation analysis.
frame = (double **)malloc(sizeof(double *) * (my ny + 1));
for(long i = 1; i <= my ny; ++ i){
frame[i] = (double *)malloc(sizeof(double) * (nsamp_window + 1));
for(long j = 1; j <= nsamp_window; ++ j)
frame[i][j] = 0.0;
} /****frame.reset (1, my ny, 1, nsamp_window);****/
brent_ixmax = nsamp_window * interpolation_depth;
} else { /* For autocorrelation analysis. */
/*
* Compute the number of samples needed for doing FFT.
* To avoid edge effects, we have to append zeroes to the window.
* The maximum lag considered for maxima is maximumLag.
* The maximum lag used in interpolation is nsamp_window * interpolation_depth.
*/
nsampFFT = 1;
while (nsampFFT < nsamp_window * (1 + interpolation_depth)) nsampFFT *= 2;
// Create buffers for autocorrelation analysis.
frame = (double **)malloc(sizeof(double *) * (my ny + 1));
for(long i = 1; i <= my ny; ++ i){
frame [i] = (double *)malloc(sizeof(double) * (nsampFFT + 1));
for(long j = 0; j <= nsampFFT; ++ j)
frame[i][j] = 0.0;
} /****frame.reset (1, my ny, 1, nsampFFT);****/
window = (double *)malloc(sizeof(double) * (nsamp_window + 1));
for(long i = 0; i <= nsamp_window; ++ i)
window[i] = 0.0;
/****window.reset (1, nsamp_window);****/
windowR = (double *)malloc(sizeof(double) * (nsampFFT + 1));
ac = (double *)malloc(sizeof(double) * (nsampFFT + 1));
for(long i = 0; i <= nsampFFT; ++ i)
windowR[i] = ac[i] = 0.0;
/****windowR.reset (1, nsampFFT); ac.reset (1, nsampFFT); ****/
NUMfft_Table_init (fftTable, nsampFFT);
/*
* A Gaussian or Hanning window is applied against phase effects.
* The Hanning window is 2 to 5 dB better for 3 periods/window.
* The Gaussian window is 25 to 29 dB better for 6 periods/window.
*/
if (method == AC_GAUSS) { /* Gaussian window. */
double imid = 0.5 * (nsamp_window + 1), edge = exp (-12.0);
for (long i = 1; i <= nsamp_window; i ++)
window[i] = (exp(-48.0*(i-imid)*(i-imid) /
(nsamp_window + 1) / (nsamp_window + 1)) - edge) / (1 - edge);
} else { /* Hanning window*/
for (long i = 1; i <= nsamp_window; i ++)
window [i] = 0.5 - 0.5 * cos (i * 2 * NUMpi / (nsamp_window + 1));
}
// Compute the normalized autocorrelation of the window.
for (long i = 1; i <= nsamp_window; i ++) windowR [i] = window [i];
NUMfft_forward (fftTable, windowR);
windowR [1] *= windowR [1]; // DC component
for (long i = 2; i < nsampFFT; i += 2) {
windowR [i] = windowR [i] * windowR [i] + windowR [i+1] * windowR [i+1];
windowR [i + 1] = 0.0; // power spectrum: square and zero
}
windowR [nsampFFT] *= windowR [nsampFFT]; // Nyquist frequency
NUMfft_backward (fftTable, windowR); // autocorrelation
for (long i = 2; i <= nsamp_window; i ++) windowR [i] /= windowR [1]; // normalize
windowR [1] = 1.0; // normalize
brent_ixmax = nsamp_window * interpolation_depth;
}
double *r = (double *) malloc( sizeof(double) * (2 * (nsamp_window + 1) + 1) );
r += nsamp_window + 1; //make "r" become a symetrical vectr
long *imax = (long *) malloc( sizeof(long) * (maxnCandidates + 1));
double *localMean = (double *) malloc( sizeof(double) * (my ny + 1));
for(iframe = 1; iframe <= nFrames; iframe ++){
Pitch_Frame pitchFrame = & thy frame[iframe];
double t = thy x1 + (iframe - 1) *(thy dx), localPeak;
long leftSample = (long) floor((t - my x1) / my dx) + 1;
long rightSample = leftSample + 1;
long startSample, endSample;
for(long channel = 1; channel <= my ny; ++ channel){ //Compute the local mean; look one longest period to both sides.
startSample = rightSample - nsamp_period;
endSample = leftSample + nsamp_period;
if ( startSample < 0 ) {
std::cout<<"StartSample < 1"<<std::endl;
std::cout<<"Sound_to_Pitch.cpp: Line 31"<<std::endl;
return NULL;
}
if (endSample > my nx){
std::cout<<"EndSample > my nx"<<std::endl;
std::cout<<"Sound_to_Pitch.cpp: Line 31.262"<<std::endl;
return NULL;
}
localMean[channel] = 0.0;
for (long i = startSample; i <= endSample; i ++) {
localMean[channel] += my z[channel][i];
}
localMean[channel] /= 2 * nsamp_period;
// Copy a window to a frame and subtract the local mean. We are going to kill the DC component before windowing.
startSample = rightSample - halfnsamp_window;
endSample = leftSample + halfnsamp_window;
if ( startSample < 1 ) {
std::cout<<"StartSample < 1"<<std::endl;
std::cout<<"Sound_to_Pitch.cpp: Line 31.281"<<std::endl;
return NULL;
}
if (endSample > my nx){
std::cout<<"EndSample > my nx"<<std::endl;
std::cout<<"Sound_to_Pitch.cpp: Line 31.287"<<std::endl;
return NULL;
}
if (method < FCC_NORMAL) {
for (long j = 1, i = startSample; j <= nsamp_window; j ++)
frame [channel] [j] = (my z [channel] [i ++] - localMean [channel]) * window [j];
for (long j = nsamp_window + 1; j <= nsampFFT; j ++)
frame [channel] [j] = 0.0;
} else {
for (long j = 1, i = startSample; j <= nsamp_window; j ++)
frame [channel] [j] = my z [channel] [i ++] - localMean [channel];
}
}
// Compute the local peak; look half a longest period to both sides.
localPeak = 0.0;
if ((startSample = halfnsamp_window + 1 - halfnsamp_period) < 1) startSample = 1;
if ((endSample = halfnsamp_window + halfnsamp_period) > nsamp_window) endSample = nsamp_window;
for (long channel = 1; channel <= my ny; channel ++) {
for (long j = startSample; j <= endSample; j ++) {
double value = fabs (frame [channel] [j]);
if (value > localPeak) localPeak = value;
}
}
pitchFrame->intensity = localPeak > globalPeak ? 1.0 : localPeak / globalPeak;
// Compute the correlation into the array 'r'.
if (method >= FCC_NORMAL) {
double startTime = t - 0.5 * (1.0 / minimumPitch + dt_window);
long localSpan = maximumLag + nsamp_window, localMaximumLag, offset;
if ((startSample = (long) floor ((startTime - my x1) / my dx)) + 1 < 1)
startSample = 1;
if (localSpan > my nx + 1 - startSample) localSpan = my nx + 1 - startSample;
localMaximumLag = localSpan - nsamp_window;
offset = startSample - 1;
double sumx2 = 0; /* Sum of squares. */
for (long channel = 1; channel <= my ny; channel ++) { ///channel = 1; channel <= my ny
double *amp = my z[channel] + offset;
for (long i = 1; i <= nsamp_window; i ++) { ///i = 1; i <= nsamp_window
double x = amp[i] - localMean[channel];
sumx2 += x * x;
}
}
double sumy2 = sumx2; /* At zero lag, these are still equal. */
r[0] = 1.0;
for (long i = 1; i <= localMaximumLag; i ++) {
double product = 0.0;
for (long channel = 1; channel <= my ny; channel ++) { ///channel = 1; channel <= my ny
double *amp = my z[channel] + offset;
double y0 = amp[i] - localMean[channel];
double yZ = amp[i + nsamp_window] - localMean[channel];
sumy2 += yZ * yZ - y0 * y0;
for (long j = 1; j <= nsamp_window; j ++) { ///j = 1; j <= nsamp_window
double x = amp[j] - localMean[channel];
double y = amp[i + j] - localMean[channel];
product += x * y;
}
}
r[- i] = r[i] = product / sqrt (sumx2 * sumy2);
}
} else {
// The FFT of the autocorrelation is the power spectrum.
for (long i = 1; i <= nsampFFT; i ++)
ac [i] = 0.0;
for (long channel = 1; channel <= my ny; channel ++) {
NUMfft_forward (fftTable, frame [channel]); /* Complex spectrum. */
ac [1] += frame [channel] [1] * frame [channel] [1]; /* DC component. */
for (long i = 2; i < nsampFFT; i += 2) {
ac [i] += frame [channel] [i] * frame [channel] [i] + frame [channel] [i+1] * frame [channel] [i+1]; /* Power spectrum. */
}
ac [nsampFFT] += frame [channel] [nsampFFT] * frame [channel] [nsampFFT]; /* Nyquist frequency. */
}
NUMfft_backward (fftTable, ac); /* Autocorrelation. */
/*
* Normalize the autocorrelation to the value with zero lag,
* and divide it by the normalized autocorrelation of the window.
*/
r [0] = 1.0;
for (long i = 1; i <= brent_ixmax; i ++)
r [- i] = r [i] = ac [i + 1] / (ac [1] * windowR [i + 1]);
}
// Create (too much) space for candidates
Pitch_Frame_init (pitchFrame, maxnCandidates);
// Register the first candidate, which is always present: voicelessness.
pitchFrame->nCandidates = 1;
pitchFrame->candidate[1].frequency = 0.0; /* Voiceless: always present. */
pitchFrame->candidate[1].strength = 0.0;
/*
* Shortcut: absolute silence is always voiceless.
* Go to next frame.
*/
if (localPeak == 0) continue;
/*
* Find the strongest maxima of the correlation of this frame,
* and register them as candidates.
*/
imax[1] = 0;
for (long i = 2; i < maximumLag && i < brent_ixmax; i ++)
if (r[i] > 0.5 * voicingThreshold && /* Not too unvoiced? */
r[i] > r[i-1] && r[i] >= r[i+1]) /* Maximum ? */
{
int place = 0;
// Use parabolic interpolation for first estimate of frequency,and sin(x)/x interpolation to compute the strength of this frequency.
double dr = 0.5 * (r[i+1] - r[i-1]);
double d2r = 2 * r[i] - r[i-1] - r[i+1];
double frequencyOfMaximum = 1 / my dx / (i + dr / d2r);
long offset = - brent_ixmax - 1;
double strengthOfMaximum = /* method & 1 ? */
NUM_interpolate_sinc (& r[offset], brent_ixmax - offset, 1 / my dx / frequencyOfMaximum - offset, 30)
/* : r [i] + 0.5 * dr * dr / d2r */;
/* High values due to short windows are to be reflected around 1. */
if (strengthOfMaximum > 1.0) strengthOfMaximum = 1.0 / strengthOfMaximum;
// Find a place for this maximum.
if (pitchFrame->nCandidates < thy maxnCandidates) { /* Is there still a free place? */
place = ++ pitchFrame->nCandidates;
} else {
/* Try the place of the weakest candidate so far. */
double weakest = 2;
for (int iweak = 2; iweak <= thy maxnCandidates; iweak ++) { //iweak = 2; iweak <= thy maxnCandidates;
/* High frequencies are to be favoured */
/* if we want to analyze a perfectly periodic signal correctly. */
double localStrength = pitchFrame->candidate[iweak].strength - octaveCost *
NUMlog2 (minimumPitch / pitchFrame->candidate[iweak].frequency);
if (localStrength < weakest) {
weakest = localStrength;
place = iweak;
}
}
/* If this maximum is weaker than the weakest candidate so far, give it no place. */
if (strengthOfMaximum - octaveCost * NUMlog2 (minimumPitch / frequencyOfMaximum) <= weakest)
place = 0;
}
if (place) { /* Have we found a place for this candidate? */
pitchFrame->candidate[place].frequency = frequencyOfMaximum;
pitchFrame->candidate[place].strength = strengthOfMaximum;
imax [place] = i;
}
}
// Second pass: for extra precision, maximize sin(x)/x interpolation ('sinc').
for (long i = 2; i <= pitchFrame->nCandidates; i ++) {
if (method != AC_HANNING || pitchFrame->candidate[i].frequency > 0.0 / my dx) {
double xmid, ymid;
long offset = - brent_ixmax - 1;
ymid = NUMimproveMaximum (& r[offset], brent_ixmax - offset, imax[i] - offset,
pitchFrame->candidate[i].frequency > 0.3 / my dx ? NUM_PEAK_INTERPOLATE_SINC700 : brent_depth, & xmid);
xmid += offset;
pitchFrame->candidate[i].frequency = 1.0 / my dx / xmid;
if (ymid > 1.0) ymid = 1.0 / ymid;
pitchFrame->candidate[i].strength = ymid;
}
}
} /* Next frame. */
Pitch_pathFinder (thee, silenceThreshold, voicingThreshold,octaveCost, octaveJumpCost,
voicedUnvoicedCost, ceiling, false);
//false: Melder_debug == 31 ? true : false Melder_debug 31: Pitch analysis: formant pulling on
return thee;
}
