Sound EEG_to_Sound_modulated (EEG me, double baseFrequency, double channelBandwidth, const wchar_t *channelRanges) {
try {
long numberOfChannels;
autoNUMvector <long> channelNumbers (NUMstring_getElementsOfRanges (channelRanges, my d_numberOfChannels, & numberOfChannels, NULL, L"channel", true), 1);
double maxFreq = baseFrequency + my d_numberOfChannels * channelBandwidth;
double samplingFrequency = 2 * maxFreq;
samplingFrequency = samplingFrequency < 44100 ? 44100 : samplingFrequency;
autoSound thee = Sound_createSimple (1, my xmax - my xmin, samplingFrequency);
for (long i = 1; i <= numberOfChannels; i++) {
long ichannel = channelNumbers[i];
double fbase = baseFrequency;// + (ichannel - 1) * channelBandwidth;
autoSound si = Sound_extractChannel (my d_sound, ichannel);
autoSpectrum spi = Sound_to_Spectrum (si.peek(), 1);
Spectrum_passHannBand (spi.peek(), 0.5, channelBandwidth - 0.5, 0.5);
autoSpectrum spi_shifted = Spectrum_shiftFrequencies (spi.peek(), fbase, samplingFrequency / 2, 30);
autoSound resampled = Spectrum_to_Sound (spi_shifted.peek());
long nx = resampled -> nx < thy nx ? resampled -> nx : thy nx;
for (long j = 1; j <= nx; j++) {
thy z[1][j] += resampled -> z[1][j];
}
}
Vector_scale (thee.peek(), 0.99);
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": no playable sound created.");
}
}
Cepstrogram Sound_to_Cepstrogram (Sound me, double analysisWidth, double dt, double maximumFrequency) {
try {
double windowDuration = 2 * analysisWidth; /* gaussian window */
long nFrames;
// Convenience: analyse the whole sound into one Cepstrogram_frame
if (windowDuration > my dx * my nx) {
windowDuration = my dx * my nx;
}
double t1, samplingFrequency = 2 * maximumFrequency;
autoSound sound = Sound_resample (me, samplingFrequency, 50);
Sampled_shortTermAnalysis (me, windowDuration, dt, & nFrames, & t1);
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
double qmin, qmax, dq, q1;
long nq;
{ // laziness: find out the proper dimensions
autoSpectrum spec = Sound_to_Spectrum (sframe.peek(), 1);
autoCepstrum cepstrum = Spectrum_to_Cepstrum (spec.peek());
qmin = cepstrum -> xmin; qmax = cepstrum -> xmax; dq = cepstrum -> dx;
q1 = cepstrum -> x1; nq = cepstrum -> nx;
}
autoCepstrogram thee = Cepstrogram_create (my xmin, my xmax, nFrames, dt, t1, qmin, qmax, nq, dq, q1);
autoMelderProgress progress (L"Cepstrogram analysis");
for (long iframe = 1; iframe <= nFrames; iframe++) {
double t = Sampled_indexToX (thee.peek(), iframe);
Sound_into_Sound (sound.peek(), sframe.peek(), t - windowDuration / 2);
Vector_subtractMean (sframe.peek());
Sounds_multiply (sframe.peek(), window.peek());
autoSpectrum spec = Sound_to_Spectrum (sframe.peek(), 1);
autoCepstrum cepstrum = Spectrum_to_Cepstrum (spec.peek());
for (long i = 1; i <= nq; i++) {
thy z[i][iframe] = cepstrum -> z[1][i];
}
if ((iframe % 10) == 1) {
Melder_progress ((double) iframe / nFrames, L"Cepstrogram analysis of frame ",
Melder_integer (iframe), L" out of ", Melder_integer (nFrames), L".");
}
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": no Cepstrogram created.");
}
}
autoComplexSpectrogram Sound_to_ComplexSpectrogram (Sound me, double windowLength, double timeStep) {
try {
double samplingFrequency = 1.0 / my dx, myDuration = my xmax - my xmin, t1;
if (windowLength > myDuration) {
Melder_throw (U"Your sound is too short:\nit should be at least as long as one window length.");
}
long nsamp_window = (long) floor (windowLength / my dx);
long halfnsamp_window = nsamp_window / 2 - 1;
nsamp_window = halfnsamp_window * 2;
if (nsamp_window < 2) {
Melder_throw (U"Your analysis window is too short: less than two samples.");
}
long numberOfFrames;
Sampled_shortTermAnalysis (me, windowLength, timeStep, &numberOfFrames, &t1);
// Compute sampling of the spectrum
long numberOfFrequencies = halfnsamp_window + 1;
double df = samplingFrequency / (numberOfFrequencies - 1);
autoComplexSpectrogram thee = ComplexSpectrogram_create (my xmin, my xmax, numberOfFrames, timeStep, t1, 0.0, 0.5 * samplingFrequency, numberOfFrequencies, df, 0.0);
//
autoSound analysisWindow = Sound_create (1, 0.0, nsamp_window * my dx, nsamp_window, my dx, 0.5 * my dx);
for (long iframe = 1; iframe <= numberOfFrames; iframe++) {
double t = Sampled_indexToX (thee.get(), iframe);
long leftSample = Sampled_xToLowIndex (me, t), rightSample = leftSample + 1;
long startSample = rightSample - halfnsamp_window;
long endSample = leftSample + halfnsamp_window;
Melder_assert (startSample >= 1);
Melder_assert (endSample <= my nx);
for (long j = 1; j <= nsamp_window; j++) {
analysisWindow -> z[1][j] = my z[1][startSample - 1 + j];
}
// window ?
autoSpectrum spec = Sound_to_Spectrum (analysisWindow.get(), 0);
thy z[1][iframe] = spec -> z[1][1] * spec -> z[1][1];
thy phase[1][iframe] = 0.0;
for (long ifreq = 2; ifreq <= numberOfFrequencies - 1; ifreq++) {
double x = spec -> z[1][ifreq], y = spec -> z[2][ifreq];
thy z[ifreq][iframe] = x * x + y * y; // power
thy phase[ifreq][iframe] = atan2 (y, x); // phase [-pi,+pi]
}
// even number of samples
thy z[numberOfFrequencies][iframe] = spec -> z[1][numberOfFrequencies] * spec -> z[1][numberOfFrequencies];
thy phase[numberOfFrequencies][iframe] = 0.0;
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": no ComplexSpectrogram created.");
}
}
Cepstrum Sound_to_Cepstrum (Sound me) {
try {
autoSpectrum spectrum = Sound_to_Spectrum (me, TRUE);
autoCepstrum thee = Spectrum_to_Cepstrum (spectrum.peek());
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": no Cepstrum calculated.");
}
}
Ltas PointProcess_Sound_to_Ltas_harmonics (PointProcess pulses, Sound sound,
long maximumHarmonic,
double shortestPeriod, double longestPeriod, double maximumPeriodFactor)
{
try {
long numberOfPeriods = pulses -> nt - 2;
autoLtas ltas = Ltas_create (maximumHarmonic, 1.0);
ltas -> xmax = maximumHarmonic;
if (numberOfPeriods < 1)
Melder_throw ("There are no periods in the point process.");
autoMelderProgress progress (L"LTAS (harmonics) analysis...");
for (long ipulse = 2; ipulse < pulses -> nt; ipulse ++) {
double leftInterval = pulses -> t [ipulse] - pulses -> t [ipulse - 1];
double rightInterval = pulses -> t [ipulse + 1] - pulses -> t [ipulse];
double intervalFactor = leftInterval > rightInterval ? leftInterval / rightInterval : rightInterval / leftInterval;
Melder_progress ((double) ipulse / pulses -> nt, L"Sound & PointProcess: To Ltas: pulse ", Melder_integer (ipulse), L" out of ", Melder_integer (pulses -> nt));
if (leftInterval >= shortestPeriod && leftInterval <= longestPeriod &&
rightInterval >= shortestPeriod && rightInterval <= longestPeriod &&
intervalFactor <= maximumPeriodFactor)
{
/*
* We have a period! Compute the spectrum.
*/
long localMaximumHarmonic;
autoSound period = Sound_extractPart (sound,
pulses -> t [ipulse] - 0.5 * leftInterval, pulses -> t [ipulse] + 0.5 * rightInterval,
kSound_windowShape_RECTANGULAR, 1.0, FALSE);
autoSpectrum spectrum = Sound_to_Spectrum (period.peek(), FALSE);
localMaximumHarmonic = maximumHarmonic < spectrum -> nx ? maximumHarmonic : spectrum -> nx;
for (long iharm = 1; iharm <= localMaximumHarmonic; iharm ++) {
double realPart = spectrum -> z [1] [iharm];
double imaginaryPart = spectrum -> z [2] [iharm];
double energy = (realPart * realPart + imaginaryPart * imaginaryPart) * 2.0 * spectrum -> dx;
ltas -> z [1] [iharm] += energy;
}
} else {
numberOfPeriods -= 1;
}
}
if (numberOfPeriods < 1)
Melder_throw (L"There are no periods in the point process.");
for (long iharm = 1; iharm <= ltas -> nx; iharm ++) {
if (ltas -> z [1] [iharm] == 0.0) {
ltas -> z [1] [iharm] = -300.0;
} else {
double energyInThisBand = ltas -> z [1] [iharm];
double powerInThisBand = energyInThisBand / (sound -> xmax - sound -> xmin);
ltas -> z [1] [iharm] = 10.0 * log10 (powerInThisBand / 4.0e-10);
}
}
return ltas.transfer();
} catch (MelderError) {
Melder_throw (sound, " & ", pulses, ": LTAS analysis (harmonics) not performed.");
}
}
autoSound Sound_filter_formula (Sound me, const char32 *formula, Interpreter interpreter) {
try {
autoSound thee = Data_copy (me);
if (my ny == 1) {
autoSpectrum spec = Sound_to_Spectrum (me, true);
Matrix_formula ((Matrix) spec.peek(), formula, interpreter, nullptr);
autoSound him = Spectrum_to_Sound (spec.peek());
NUMvector_copyElements (his z [1], thy z [1], 1, thy nx);
} else {
for (long ichan = 1; ichan <= my ny; ichan ++) {
autoSound channel = Sound_extractChannel (me, ichan);
autoSpectrum spec = Sound_to_Spectrum (channel.peek(), true);
Matrix_formula ((Matrix) spec.peek(), formula, interpreter, nullptr);
autoSound him = Spectrum_to_Sound (spec.peek());
NUMvector_copyElements (his z [1], thy z [ichan], 1, thy nx);
}
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": not filtered (with formula).");
}
}
Ltas Sound_to_Ltas (Sound me, double bandwidth) {
try {
autoSpectrum thee = Sound_to_Spectrum (me, TRUE);
autoLtas him = Spectrum_to_Ltas (thee.peek(), bandwidth);
double correction = -10.0 * log10 (thy dx * my nx * my dx);
for (long iband = 1; iband <= his nx; iband ++) {
his z [1] [iband] += correction;
}
return him.transfer();
} catch (MelderError) {
Melder_throw (me, ": LTAS analysis not performed.");
}
}
autoSound Sound_filter_stopHannBand (Sound me, double fmin, double fmax, double smooth) {
try {
autoSound thee = Data_copy (me);
if (my ny == 1) {
autoSpectrum spec = Sound_to_Spectrum (me, true);
Spectrum_stopHannBand (spec.peek(), fmin, fmax, smooth);
autoSound him = Spectrum_to_Sound (spec.peek());
NUMvector_copyElements (his z [1], thy z [1], 1, thy nx);
} else {
for (long ichan = 1; ichan <= my ny; ichan ++) {
autoSound channel = Sound_extractChannel (me, ichan);
autoSpectrum spec = Sound_to_Spectrum (channel.peek(), true);
Spectrum_stopHannBand (spec.peek(), fmin, fmax, smooth);
autoSound him = Spectrum_to_Sound (spec.peek());
NUMvector_copyElements (his z [1], thy z [ichan], 1, thy nx);
}
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": not filtered (stop Hann band).");
}
}
Sound EEG_to_Sound_frequencyShifted (EEG me, long channel, double frequencyShift, double samplingFrequency, double maxAmp) {
try {
autoSound si = Sound_extractChannel (my d_sound, channel);
autoSpectrum spi = Sound_to_Spectrum (si.peek(), 1);
autoSpectrum spi_shifted = Spectrum_shiftFrequencies (spi.peek(), frequencyShift, samplingFrequency / 2, 30);
autoSound thee = Spectrum_to_Sound (spi_shifted.peek());
if (maxAmp > 0) {
Vector_scale (thee.peek(), maxAmp);
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": channel not converted to sound.");
}
}
autoCochleagram Sound_to_Cochleagram (Sound me, double dt, double df, double dt_window, double forwardMaskingTime) {
try {
double duration = my nx * my dx;
long nFrames = 1 + (long) floor ((duration - dt_window) / dt);
long nsamp_window = (long) floor (dt_window / my dx), halfnsamp_window = nsamp_window / 2 - 1;
long nf = lround (25.6 / df);
double dampingFactor = forwardMaskingTime > 0.0 ? exp (- dt / forwardMaskingTime) : 0.0; // default 30 ms
double integrationCorrection = 1.0 - dampingFactor;
nsamp_window = halfnsamp_window * 2;
if (nFrames < 2) return autoCochleagram ();
double t1 = my x1 + 0.5 * (duration - my dx - (nFrames - 1) * dt); // centre of first frame
autoCochleagram thee = Cochleagram_create (my xmin, my xmax, nFrames, dt, t1, df, nf);
autoSound window = Sound_createSimple (1, nsamp_window * my dx, 1.0 / my dx);
for (long iframe = 1; iframe <= nFrames; iframe ++) {
double t = Sampled_indexToX (thee.get(), iframe);
long leftSample = Sampled_xToLowIndex (me, t);
long rightSample = leftSample + 1;
long startSample = rightSample - halfnsamp_window;
long endSample = rightSample + halfnsamp_window;
if (startSample < 1) {
Melder_casual (U"Start sample too small: ", startSample,
U" instead of 1.");
startSample = 1;
}
if (endSample > my nx) {
Melder_casual (U"End sample too small: ", endSample,
U" instead of ", my nx,
U".");
endSample = my nx;
}
/* Copy a window to a frame. */
for (long i = 1; i <= nsamp_window; i ++)
window -> z [1] [i] =
( my ny == 1 ? my z[1][i+startSample-1] : 0.5 * (my z[1][i+startSample-1] + my z[2][i+startSample-1]) ) *
(0.5 - 0.5 * cos (2.0 * NUMpi * i / (nsamp_window + 1)));
autoSpectrum spec = Sound_to_Spectrum (window.get(), true);
autoExcitation excitation = Spectrum_to_Excitation (spec.get(), df);
for (long ifreq = 1; ifreq <= nf; ifreq ++)
thy z [ifreq] [iframe] = excitation -> z [1] [ifreq] + ( iframe > 1 ? dampingFactor * thy z [ifreq] [iframe - 1] : 0 );
}
for (long iframe = 1; iframe <= nFrames; iframe ++)
for (long ifreq = 1; ifreq <= nf; ifreq ++)
thy z [ifreq] [iframe] *= integrationCorrection;
return thee;
} catch (MelderError) {
Melder_throw (me, U": not converted to Cochleagram.");
}
}
autoPitch Pitch_smooth (Pitch me, double bandWidth) {
try {
autoPitch interp = Pitch_interpolate (me);
autoMatrix matrix1 = Pitch_to_Matrix (interp.peek());
autoSound sound1 = Sound_create (1, 2 * matrix1->xmin - matrix1->xmax, 2 * matrix1->xmax - matrix1->xmin,
3 * matrix1->nx, matrix1->dx, matrix1->x1 - 2 * matrix1->nx * matrix1->dx);
long firstVoiced = 0, lastVoiced = 0;
for (long i = 1; i <= matrix1 -> nx; i ++) {
double f = matrix1 -> z [1] [i];
if (f != 0.0) {
if (! firstVoiced) firstVoiced = i;
lastVoiced = i;
sound1 -> z [1] [i + matrix1 -> nx] = f;
}
}
/* Extrapolate. */
double fextrap = matrix1 -> z [1] [firstVoiced];
firstVoiced += matrix1 -> nx;
for (long i = 1; i < firstVoiced; i ++)
sound1 -> z [1] [i] = fextrap;
fextrap = matrix1 -> z [1] [lastVoiced];
lastVoiced += matrix1 -> nx;
for (long i = lastVoiced + 1; i <= sound1 -> nx; i ++)
sound1 -> z [1] [i] = fextrap;
/* Smooth. */
autoSpectrum spectrum = Sound_to_Spectrum (sound1.peek(), true);
for (long i = 1; i <= spectrum -> nx; i ++) {
double f = (i - 1) * spectrum -> dx, fT = f / bandWidth, factor = exp (- fT * fT);
spectrum -> z [1] [i] *= factor;
spectrum -> z [2] [i] *= factor;
}
autoSound sound2 = Spectrum_to_Sound (spectrum.peek());
autoMatrix matrix2 = Matrix_create (my xmin, my xmax, my nx, my dx, my x1, 1, 1, 1, 1, 1);
for (long i = 1; i <= my nx; i ++) {
double originalF0 = my frame [i]. candidate [1]. frequency;
matrix2 -> z [1] [i] = originalF0 > 0.0 && originalF0 < my ceiling ?
sound2 -> z [1] [i + matrix2 -> nx] : 0.0;
}
autoPitch thee = Matrix_to_Pitch (matrix2.peek());
thy ceiling = my ceiling;
return thee;
} catch (MelderError) {
Melder_throw (me, U": not smoothed.");
}
}
Ltas Sound_to_Ltas (Sound me, double bandwidth) {
Spectrum thee = NULL;
Ltas him = NULL;
long iband;
double correction;
thee = Sound_to_Spectrum (me, TRUE); cherror
him = Spectrum_to_Ltas (thee, bandwidth); cherror
correction = -10 * log10 (thy dx * my nx * my dx);
for (iband = 1; iband <= his nx; iband ++) {
his z [1] [iband] += correction;
}
end:
iferror forget (him);
forget (thee);
return him;
}
PowerCepstrogram Sound_to_PowerCepstrogram (Sound me, double pitchFloor, double dt, double maximumFrequency, double preEmphasisFrequency) {
try {
// minimum analysis window has 3 periods of lowest pitch
double analysisWidth = 3 / pitchFloor;
double windowDuration = 2 * analysisWidth; /* gaussian window */
long nFrames;
// Convenience: analyse the whole sound into one Cepstrogram_frame
if (windowDuration > my dx * my nx) {
windowDuration = my dx * my nx;
}
double t1, samplingFrequency = 2 * maximumFrequency;
autoSound sound = Sound_resample (me, samplingFrequency, 50);
Sound_preEmphasis (sound.peek(), preEmphasisFrequency);
Sampled_shortTermAnalysis (me, windowDuration, dt, & nFrames, & t1);
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
// find out the size of the FFT
long nfft = 2;
while (nfft < sframe -> nx) nfft *= 2;
long nq = nfft / 2 + 1;
double qmax = 0.5 * nfft / samplingFrequency, dq = qmax / (nq - 1);
autoPowerCepstrogram thee = PowerCepstrogram_create (my xmin, my xmax, nFrames, dt, t1, 0, qmax, nq, dq, 0);
autoMelderProgress progress (L"Cepstrogram analysis");
for (long iframe = 1; iframe <= nFrames; iframe++) {
double t = Sampled_indexToX (thee.peek(), iframe);
Sound_into_Sound (sound.peek(), sframe.peek(), t - windowDuration / 2);
Vector_subtractMean (sframe.peek());
Sounds_multiply (sframe.peek(), window.peek());
autoSpectrum spec = Sound_to_Spectrum (sframe.peek(), 1); // FFT yes
autoPowerCepstrum cepstrum = Spectrum_to_PowerCepstrum (spec.peek());
for (long i = 1; i <= nq; i++) {
thy z[i][iframe] = cepstrum -> z[1][i];
}
if ((iframe % 10) == 1) {
Melder_progress ((double) iframe / nFrames, L"PowerCepstrogram analysis of frame ",
Melder_integer (iframe), L" out of ", Melder_integer (nFrames), L".");
}
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": no PowerCepstrogram created.");
}
}
Spectrum Cepstrum_to_Spectrum (Cepstrum me) {
try {
autoSound x = Sound_create (1, my xmin, my xmax, my nx, my dx, my x1);
NUMvector_copyElements (my z[1], x -> z[1], 1, my nx);
autoSpectrum thee = Sound_to_Spectrum (x.peek(), TRUE);
for (long i = 1; i <= thy nx; i++) {
double ar = exp (thy z[1][i]);
double ai = thy z[2][i];
thy z[1][i] = ar * cos (ai);
thy z[2][i] = ar * sin (ai);
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": no Spectrum created.");
}
}
Spectrum Spectrum_cepstralSmoothing (Spectrum me, double bandWidth) {
try {
/*
* dB-spectrum is log (power).
*/
autoSpectrum dBspectrum = Data_copy (me);
double *re = dBspectrum -> z [1], *im = dBspectrum -> z [2];
for (long i = 1; i <= dBspectrum -> nx; i ++) {
re [i] = log (re [i] * re [i] + im [i] * im [i] + 1e-300);
im [i] = 0.0;
}
/*
* Cepstrum is Fourier transform of dB-spectrum.
*/
autoSound cepstrum = Spectrum_to_Sound (dBspectrum.peek());
/*
* Multiply cepstrum by a Gaussian.
*/
double factor = - bandWidth * bandWidth;
for (long i = 1; i <= cepstrum -> nx; i ++) {
double t = (i - 1) * cepstrum -> dx;
cepstrum -> z [1] [i] *= exp (factor * t * t) * ( i == 1 ? 1 : 2 );
}
/*
* Smoothed power spectrum is original power spectrum convolved with a Gaussian.
*/
autoSpectrum thee = Sound_to_Spectrum (cepstrum.peek(), TRUE);
/*
* Convert power spectrum back into a "complex" spectrum without phase information.
*/
re = thy z [1], im = thy z [2];
for (long i = 1; i <= thy nx; i ++) {
re [i] = exp (0.5 * re [i]); // i.e., sqrt (exp (re [i]))
im [i] = 0.0;
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": cepstral smoothing not computed.");
}
}
autoSpectrum Cepstrum_to_Spectrum (Cepstrum me) { //TODO power cepstrum
try {
autoCepstrum cepstrum = Data_copy (me);
cepstrum -> z[1][1] = my z[1][1];
for (long i = 2; i <= cepstrum -> nx; i++) {
cepstrum -> z[1][i] = 2 * my z[1][i];
}
autoSpectrum thee = Sound_to_Spectrum ((Sound) cepstrum.peek(), 1);
double *re = thy z[1], *im = thy z[2];
for (long i = 1; i <= thy nx; i ++) {
re[i] = exp (0.5 * re[i]); // i.e., sqrt (exp(re [i]))
im[i] = 0.0;
}
return thee;
} catch (MelderError) {
Melder_throw (me, U": no Spectrum created.");
}
}
Ltas PointProcess_Sound_to_Ltas (PointProcess pulses, Sound sound,
double maximumFrequency, double bandWidth,
double shortestPeriod, double longestPeriod, double maximumPeriodFactor)
{
Ltas ltas = NULL, numbers = NULL;
Sound period = NULL;
Spectrum spectrum = NULL;
long numberOfPeriods = pulses -> nt - 2, ipulse, ifreq, iband, totalNumberOfEnergies = 0;
ltas = Ltas_create (maximumFrequency / bandWidth, bandWidth); cherror
ltas -> xmax = maximumFrequency;
numbers = (structLtas *)Data_copy (ltas);
if (numberOfPeriods < 1) error1 (L"Cannot compute an Ltas if there are no periods in the point process.")
for (ipulse = 2; ipulse < pulses -> nt; ipulse ++) {
double leftInterval = pulses -> t [ipulse] - pulses -> t [ipulse - 1];
double rightInterval = pulses -> t [ipulse + 1] - pulses -> t [ipulse];
double intervalFactor = leftInterval > rightInterval ? leftInterval / rightInterval : rightInterval / leftInterval;
Melder_progress4 ((double) ipulse / pulses -> nt, L"Sound & PointProcess: To Ltas: pulse ", Melder_integer (ipulse), L" out of ", Melder_integer (pulses -> nt));
if (leftInterval >= shortestPeriod && leftInterval <= longestPeriod &&
rightInterval >= shortestPeriod && rightInterval <= longestPeriod &&
intervalFactor <= maximumPeriodFactor)
{
/*
* We have a period! Compute the spectrum.
*/
period = Sound_extractPart (sound,
pulses -> t [ipulse] - 0.5 * leftInterval, pulses -> t [ipulse] + 0.5 * rightInterval,
kSound_windowShape_RECTANGULAR, 1.0, FALSE); cherror
spectrum = Sound_to_Spectrum (period, FALSE); cherror
for (ifreq = 1; ifreq <= spectrum -> nx; ifreq ++) {
double frequency = spectrum -> xmin + (ifreq - 1) * spectrum -> dx;
double realPart = spectrum -> z [1] [ifreq];
double imaginaryPart = spectrum -> z [2] [ifreq];
double energy = (realPart * realPart + imaginaryPart * imaginaryPart) * 2.0 * spectrum -> dx /* OLD: * sound -> nx */;
iband = ceil (frequency / bandWidth);
if (iband >= 1 && iband <= ltas -> nx) {
ltas -> z [1] [iband] += energy;
numbers -> z [1] [iband] += 1;
totalNumberOfEnergies += 1;
}
}
forget (spectrum);
forget (period);
} else {
static autoSpectrum Sound_to_Spectrum_power (Sound me) {
try {
autoSpectrum thee = Sound_to_Spectrum (me, true);
double scale = 2.0 * thy dx / (my xmax - my xmin);
// factor '2' because we combine positive and negative frequencies
// thy dx : width of frequency bin
// my xmax - my xmin : duration of sound
double *re = thy z[1], *im = thy z[2];
for (long i = 1; i <= thy nx; i++) {
double power = scale * (re[i] * re[i] + im[i] * im [i]);
re[i] = power; im[i] = 0;
}
// Correction of frequency bins at 0 Hz and nyquist: don't count for two.
re[1] *= 0.5; re[thy nx] *= 0.5;
return thee;
} catch (MelderError) {
Melder_throw (me, U": no Spectrum with spectral power created.");
}
}
static Matrix Sound_to_spectralpower (Sound me) {
try {
autoSpectrum s = Sound_to_Spectrum (me, TRUE);
autoMatrix thee = Matrix_create (s -> xmin, s -> xmax, s -> nx, s -> dx, s -> x1, 1, 1, 1, 1, 1);
double scale = 2.0 * s -> dx / (my xmax - my xmin);
// factor '2' because of positive and negative frequencies
// s -> dx : width of frequncy bin
// my xmax - my xmin : duration of sound
double *z = thy z[1], *re = s -> z[1], *im = s -> z[2];
for (long i = 1; i <= s -> nx; i++) {
z[i] = scale * (re[i] * re[i] + im[i] * im [i]);
}
// Frequency bins at 0 Hz and nyquist don't count for two.
z[1] *= 0.5;
z[s -> nx] *= 0.5;
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": no Matrix with spectral power created.");
}
}
autoMatrix Spectrum_unwrap (Spectrum me) {
try {
struct tribolet_struct tbs;
int remove_linear_part = 1;
long nfft = 2;
while (nfft < my nx - 1) {
nfft *= 2;
}
nfft *= 2;
if (nfft / 2 != my nx - 1) {
Melder_throw (U"Dimension of Spectrum is not (power of 2 - 1).");
}
autoSound x = Spectrum_to_Sound (me);
autoSound nx = Data_copy (x.get());
for (long i = 1; i <= x -> nx; i++) {
nx -> z[1][i] *= (i - 1);
}
autoSpectrum snx = Sound_to_Spectrum (nx.get(), 1);
autoMatrix thee = Matrix_create (my xmin, my xmax, my nx, my dx, my x1, 1, 2, 2, 1, 1);
// Common variables.
tbs.thlinc = THLINC;
tbs.thlcon = THLCON;
tbs.x = x -> z[1];
tbs.nx = x -> nx;
tbs.l = (long) floor (pow (2, EXP2) + 0.1);
tbs.ddf = NUM2pi / ( (tbs.l) * nfft);
tbs.reverse_sign = my z[1][1] < 0;
tbs.count = 0;
// Reuse snx : put phase derivative (d/df) in imaginary part.
tbs.dvtmn2 = 0;
for (long i = 1; i <= my nx; i ++) {
double xr = my z[1][i], xi = my z[2][i];
double nxr = snx -> z[1][i], nxi = snx -> z[2][i];
double xmsq = xr * xr + xi * xi;
double pdvt = PHADVT (xr, xi, nxr, nxi, xmsq);
thy z[1][i] = xmsq;
snx -> z[2][i] = pdvt;
tbs.dvtmn2 += pdvt;
}
tbs.dvtmn2 = (2 * tbs.dvtmn2 - snx -> z[2][1] - snx -> z[2][my nx]) / (my nx - 1);
autoMelderProgress progress (U"Phase unwrapping");
double pphase = 0, phase = 0;
double ppdvt = snx -> z[2][1];
thy z[2][1] = PPVPHA (my z[1][1], my z[2][1], tbs.reverse_sign);
for (long i = 2; i <= my nx; i ++) {
double pfreq = NUM2pi * (i - 1) / nfft;
double pdvt = snx -> z[2][i];
double ppv = PPVPHA (my z[1][i], my z[2][i], tbs.reverse_sign);
phase = phase_unwrap (&tbs, pfreq, ppv, pdvt, &pphase, &ppdvt);
ppdvt = pdvt;
thy z[2][i] = pphase = phase;
Melder_progress ( (double) i / my nx, i,
U" unwrapped phases from ", my nx, U".");
}
long iphase = (long) floor (phase / NUMpi + 0.1); // ppgb: better than truncation toward zero
if (remove_linear_part) {
phase /= my nx - 1;
for (long i = 2; i <= my nx; i ++) {
thy z[2][i] -= phase * (i - 1);
}
}
Melder_information (U"Number of spectral values: ", tbs.count);
Melder_information (U" iphase = ", iphase);
return thee;
} catch (MelderError) {
Melder_throw (me, U": not unwrapped.");
}
}
Ltas PointProcess_Sound_to_Ltas (PointProcess pulses, Sound sound,
double maximumFrequency, double bandWidth,
double shortestPeriod, double longestPeriod, double maximumPeriodFactor)
{
try {
long numberOfPeriods = pulses -> nt - 2, totalNumberOfEnergies = 0;
autoLtas ltas = Ltas_create (maximumFrequency / bandWidth, bandWidth);
ltas -> xmax = maximumFrequency;
autoLtas numbers = Data_copy (ltas.peek());
if (numberOfPeriods < 1)
Melder_throw ("Cannot compute an Ltas if there are no periods in the point process.");
autoMelderProgress progress (L"Ltas analysis...");
for (long ipulse = 2; ipulse < pulses -> nt; ipulse ++) {
double leftInterval = pulses -> t [ipulse] - pulses -> t [ipulse - 1];
double rightInterval = pulses -> t [ipulse + 1] - pulses -> t [ipulse];
double intervalFactor = leftInterval > rightInterval ? leftInterval / rightInterval : rightInterval / leftInterval;
Melder_progress ((double) ipulse / pulses -> nt, L"Sound & PointProcess: To Ltas: pulse ", Melder_integer (ipulse), L" out of ", Melder_integer (pulses -> nt));
if (leftInterval >= shortestPeriod && leftInterval <= longestPeriod &&
rightInterval >= shortestPeriod && rightInterval <= longestPeriod &&
intervalFactor <= maximumPeriodFactor)
{
/*
* We have a period! Compute the spectrum.
*/
autoSound period = Sound_extractPart (sound,
pulses -> t [ipulse] - 0.5 * leftInterval, pulses -> t [ipulse] + 0.5 * rightInterval,
kSound_windowShape_RECTANGULAR, 1.0, FALSE);
autoSpectrum spectrum = Sound_to_Spectrum (period.peek(), FALSE);
for (long ifreq = 1; ifreq <= spectrum -> nx; ifreq ++) {
double frequency = spectrum -> xmin + (ifreq - 1) * spectrum -> dx;
double realPart = spectrum -> z [1] [ifreq];
double imaginaryPart = spectrum -> z [2] [ifreq];
double energy = (realPart * realPart + imaginaryPart * imaginaryPart) * 2.0 * spectrum -> dx /* OLD: * sound -> nx */;
long iband = ceil (frequency / bandWidth);
if (iband >= 1 && iband <= ltas -> nx) {
ltas -> z [1] [iband] += energy;
numbers -> z [1] [iband] += 1;
totalNumberOfEnergies += 1;
}
}
} else {
numberOfPeriods -= 1;
}
}
if (numberOfPeriods < 1)
Melder_throw ("There are no periods in the point process.");
for (long iband = 1; iband <= ltas -> nx; iband ++) {
if (numbers -> z [1] [iband] == 0.0) {
ltas -> z [1] [iband] = NUMundefined;
} else {
/*
* Each bin now contains a total energy in Pa2 sec.
* To convert this to power density, we
*/
double totalEnergyInThisBand = ltas -> z [1] [iband];
if (0 /* i.e. if you just want to have a spectrum of the voiced parts... */) {
double energyDensityInThisBand = totalEnergyInThisBand / ltas -> dx;
double powerDensityInThisBand = energyDensityInThisBand / (sound -> xmax - sound -> xmin);
ltas -> z [1] [iband] = 10.0 * log10 (powerDensityInThisBand / 4.0e-10);
} else {
/*
* And this is what we really want. The total energy has to be redistributed.
*/
double meanEnergyInThisBand = totalEnergyInThisBand / numbers -> z [1] [iband];
double meanNumberOfEnergiesPerBand = (double) totalNumberOfEnergies / ltas -> nx;
double redistributedEnergyInThisBand = meanEnergyInThisBand * meanNumberOfEnergiesPerBand;
double redistributedEnergyDensityInThisBand = redistributedEnergyInThisBand / ltas -> dx;
double redistributedPowerDensityInThisBand = redistributedEnergyDensityInThisBand / (sound -> xmax - sound -> xmin);
ltas -> z [1] [iband] = 10.0 * log10 (redistributedPowerDensityInThisBand / 4.0e-10);
/* OLD: ltas -> z [1] [iband] = 10.0 * log10 (ltas -> z [1] [iband] / numbers -> z [1] [iband] * sound -> nx);*/
}
}
}
for (long iband = 1; iband <= ltas -> nx; iband ++) {
if (ltas -> z [1] [iband] == NUMundefined) {
long ibandleft = iband - 1, ibandright = iband + 1;
while (ibandleft >= 1 && ltas -> z [1] [ibandleft] == NUMundefined) ibandleft --;
while (ibandright <= ltas -> nx && ltas -> z [1] [ibandright] == NUMundefined) ibandright ++;
if (ibandleft < 1 && ibandright > ltas -> nx)
Melder_throw ("Cannot create an Ltas without energy in any bins.");
if (ibandleft < 1) {
ltas -> z [1] [iband] = ltas -> z [1] [ibandright];
} else if (ibandright > ltas -> nx) {
ltas -> z [1] [iband] = ltas -> z [1] [ibandleft];
} else {
double frequency = ltas -> x1 + (iband - 1) * ltas -> dx;
double fleft = ltas -> x1 + (ibandleft - 1) * ltas -> dx;
double fright = ltas -> x1 + (ibandright - 1) * ltas -> dx;
ltas -> z [1] [iband] = ((fright - frequency) * ltas -> z [1] [ibandleft]
+ (frequency - fleft) * ltas -> z [1] [ibandright]) / (fright - fleft);
}
}
}
return ltas.transfer();
} catch (MelderError) {
Melder_throw (sound, " & ", pulses, ": LTAS analysis not performed.");
}
}
Pitch Sound_to_Pitch_shs (Sound me, double timeStep, double minimumPitch,
double maximumFrequency, double ceiling, long maxnSubharmonics, long maxnCandidates,
double compressionFactor, long nPointsPerOctave) {
try {
double firstTime, newSamplingFrequency = 2 * maximumFrequency;
double windowDuration = 2 / minimumPitch, halfWindow = windowDuration / 2;
double atans = nPointsPerOctave * NUMlog2 (65.0 / 50.0) - 1;
// Number of speech samples in the downsampled signal in each frame:
// 100 for windowDuration == 0.04 and newSamplingFrequency == 2500
long nx = lround (windowDuration * newSamplingFrequency);
// The minimum number of points for the fft is 256.
long nfft = 1;
while ( (nfft *= 2) < nx || nfft <= 128) {
;
}
long nfft2 = nfft / 2 + 1;
double frameDuration = nfft / newSamplingFrequency;
double df = newSamplingFrequency / nfft;
// The number of points on the octave scale
double fminl2 = NUMlog2 (minimumPitch), fmaxl2 = NUMlog2 (maximumFrequency);
long nFrequencyPoints = (long) floor ((fmaxl2 - fminl2) * nPointsPerOctave);
double dfl2 = (fmaxl2 - fminl2) / (nFrequencyPoints - 1);
autoSound sound = Sound_resample (me, newSamplingFrequency, 50);
long numberOfFrames;
Sampled_shortTermAnalysis (sound.peek(), windowDuration, timeStep, &numberOfFrames, &firstTime);
autoSound frame = Sound_createSimple (1, frameDuration, newSamplingFrequency);
autoSound hamming = Sound_createHamming (nx / newSamplingFrequency, newSamplingFrequency);
autoPitch thee = Pitch_create (my xmin, my xmax, numberOfFrames, timeStep, firstTime,
ceiling, maxnCandidates);
autoNUMvector<double> cc (1, numberOfFrames);
autoNUMvector<double> specAmp (1, nfft2);
autoNUMvector<double> fl2 (1, nfft2);
autoNUMvector<double> yv2 (1, nfft2);
autoNUMvector<double> arctg (1, nFrequencyPoints);
autoNUMvector<double> al2 (1, nFrequencyPoints);
Melder_assert (frame->nx >= nx);
Melder_assert (hamming->nx == nx);
// Compute the absolute value of the globally largest amplitude w.r.t. the global mean.
double globalMean, globalPeak;
Sound_localMean (sound.peek(), sound -> xmin, sound -> xmax, &globalMean);
Sound_localPeak (sound.peek(), sound -> xmin, sound -> xmax, globalMean, &globalPeak);
/*
For the cubic spline interpolation we need the frequencies on an octave
scale, i.e., a log2 scale. All frequencies must be DIFFERENT, otherwise
the cubic spline interpolation will give corrupt results.
Because log2(f==0) is not defined, we use the heuristic: f[2]-f[1] == f[3]-f[2].
*/
for (long i = 2; i <= nfft2; i++) {
fl2[i] = NUMlog2 ( (i - 1) * df);
}
fl2[1] = 2 * fl2[2] - fl2[3];
// Calculate frequencies regularly spaced on a log2-scale and
// the frequency weighting function.
for (long i = 1; i <= nFrequencyPoints; i++) {
arctg[i] = 0.5 + atan (3 * (i - atans) / nPointsPerOctave) / NUMpi;
}
// Perform the analysis on all frames.
for (long i = 1; i <= numberOfFrames; i++) {
Pitch_Frame pitchFrame = &thy frame[i];
double hm = 1, f0, pitch_strength, localMean, localPeak;
double tmid = Sampled_indexToX (thee.peek(), i); /* The center of this frame */
long nx_tmp = frame -> nx;
// Copy a frame from the sound, apply a hamming window. Get local 'intensity'
frame -> nx = nx; /*begin vies */
Sound_into_Sound (sound.peek(), frame.peek(), tmid - halfWindow);
Sounds_multiply (frame.peek(), hamming.peek());
Sound_localMean (sound.peek(), tmid - 3 * halfWindow, tmid + 3 * halfWindow, &localMean);
Sound_localPeak (sound.peek(), tmid - halfWindow, tmid + halfWindow, localMean, &localPeak);
pitchFrame -> intensity = localPeak > globalPeak ? 1 : localPeak / globalPeak;
frame -> nx = nx_tmp; /* einde vies */
// Get the Fourier spectrum.
autoSpectrum spec = Sound_to_Spectrum (frame.peek(), 1);
Melder_assert (spec->nx == nfft2);
// From complex spectrum to amplitude spectrum.
for (long j = 1; j <= nfft2; j++) {
double rs = spec -> z[1][j], is = spec -> z[2][j];
specAmp[j] = sqrt (rs * rs + is * is);
}
// Enhance the peaks in the spectrum.
spec_enhance_SHS (specAmp.peek(), nfft2);
// Smooth the enhanced spectrum.
spec_smoooth_SHS (specAmp.peek(), nfft2);
// Go to a logarithmic scale and perform cubic spline interpolation to get
// spectral values for the increased number of frequency points.
NUMspline (fl2.peek(), specAmp.peek(), nfft2, 1e30, 1e30, yv2.peek());
for (long j = 1; j <= nFrequencyPoints; j++) {
double f = fminl2 + (j - 1) * dfl2;
NUMsplint (fl2.peek(), specAmp.peek(), yv2.peek(), nfft2, f, &al2[j]);
}
// Multiply by frequency selectivity of the auditory system.
for (long j = 1; j <= nFrequencyPoints; j++) al2[j] = al2[j] > 0 ?
al2[j] * arctg[j] : 0;
// The subharmonic summation. Shift spectra in octaves and sum.
Pitch_Frame_init (pitchFrame, maxnCandidates);
autoNUMvector<double> sumspec (1, nFrequencyPoints);
pitchFrame -> nCandidates = 0; /* !!!!! */
for (long m = 1; m <= maxnSubharmonics + 1; m++) {
long kb = 1 + (long) floor (nPointsPerOctave * NUMlog2 (m));
for (long k = kb; k <= nFrequencyPoints; k++) {
sumspec[k - kb + 1] += al2[k] * hm;
}
hm *= compressionFactor;
}
// First register the voiceless candidate (always present).
Pitch_Frame_addPitch (pitchFrame, 0, 0, maxnCandidates);
/*
Get the best local estimates for the pitch as the maxima of the
subharmonic sum spectrum by parabolic interpolation on three points:
The formula for a parabole with a maximum is:
y(x) = a - b (x - c)^2 with a, b, c >= 0
The three points are (-x, y1), (0, y2) and (x, y3).
The solution for a (the maximum) and c (the position) is:
a = (2 y1 (4 y2 + y3) - y1^2 - (y3 - 4 y2)^2)/( 8 (y1 - 2 y2 + y3)
c = dx (y1 - y3) / (2 (y1 - 2 y2 + y3))
(b = (2 y2 - y1 - y3) / (2 dx^2) )
*/
for (long k = 2; k <= nFrequencyPoints - 1; k++) {
double y1 = sumspec[k - 1], y2 = sumspec[k], y3 = sumspec[k + 1];
if (y2 > y1 && y2 >= y3) {
double denum = y1 - 2 * y2 + y3, tmp = y3 - 4 * y2;
double x = dfl2 * (y1 - y3) / (2 * denum);
double f = pow (2, fminl2 + (k - 1) * dfl2 + x);
double strength = (2 * y1 * (4 * y2 + y3) - y1 * y1 - tmp * tmp) / (8 * denum);
Pitch_Frame_addPitch (pitchFrame, f, strength, maxnCandidates);
}
}
/*
Check whether f0 corresponds to an actual periodicity T = 1 / f0:
correlate two signal periods of duration T, one starting at the
middle of the interval and one starting T seconds before.
If there is periodicity the correlation coefficient should be high.
However, some sounds do not show any regularity, or very low
frequency and regularity, and nevertheless have a definite
pitch, e.g. Shepard sounds.
*/
Pitch_Frame_getPitch (pitchFrame, &f0, &pitch_strength);
if (f0 > 0) {
cc[i] = Sound_correlateParts (sound.peek(), tmid - 1.0 / f0, tmid, 1.0 / f0);
}
}
// Base V/UV decision on correlation coefficients.
// Resize the pitch strengths w.r.t. the cc.
double vuvCriterium = 0.52;
for (long i = 1; i <= numberOfFrames; i++) {
Pitch_Frame_resizeStrengths (& thy frame[i], cc[i], vuvCriterium);
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, U": no Pitch (shs) created.");
}
}
Sound Sound_deepenBandModulation (Sound me, double enhancement_dB,
double flow, double fhigh, double slowModulation, double fastModulation, double bandSmoothing)
{
try {
autoSound thee = Data_copy (me);
double maximumFactor = pow (10, enhancement_dB / 20), alpha = sqrt (log (2.0));
double alphaslow = alpha / slowModulation, alphafast = alpha / fastModulation;
for (long channel = 1; channel <= my ny; channel ++) {
autoSound channelSound = Sound_extractChannel (me, channel);
autoSpectrum orgspec = Sound_to_Spectrum (channelSound.peek(), true);
/*
* Keep the part of the sound that is outside the filter bank.
*/
autoSpectrum spec = Data_copy (orgspec.peek());
Spectrum_stopHannBand (spec.peek(), flow, fhigh, bandSmoothing);
autoSound filtered = Spectrum_to_Sound (spec.peek());
long n = thy nx;
double *amp = thy z [channel];
for (long i = 1; i <= n; i ++) amp [i] = filtered -> z [1] [i];
autoMelderProgress progress (U"Deepen band modulation...");
double fmin = flow;
while (fmin < fhigh) {
/*
* Take a one-bark frequency band.
*/
double fmid_bark = NUMhertzToBark (fmin) + 0.5, ceiling;
double fmax = NUMbarkToHertz (NUMhertzToBark (fmin) + 1);
if (fmax > fhigh) fmax = fhigh;
Melder_progress (fmin / fhigh, U"Band: ", Melder_fixed (fmin, 0), U" ... ", Melder_fixed (fmax, 0), U" Hz");
NUMmatrix_copyElements (orgspec -> z, spec -> z, 1, 2, 1, spec -> nx);
Spectrum_passHannBand (spec.peek(), fmin, fmax, bandSmoothing);
autoSound band = Spectrum_to_Sound (spec.peek());
/*
* Compute a relative intensity contour.
*/
autoSound intensity = Data_copy (band.peek());
n = intensity -> nx;
amp = intensity -> z [1];
for (long i = 1; i <= n; i ++) amp [i] = 10 * log10 (amp [i] * amp [i] + 1e-6);
autoSpectrum intensityFilter = Sound_to_Spectrum (intensity.peek(), true);
n = intensityFilter -> nx;
for (long i = 1; i <= n; i ++) {
double frequency = intensityFilter -> x1 + (i - 1) * intensityFilter -> dx;
double slow = alphaslow * frequency, fast = alphafast * frequency;
double factor = exp (- fast * fast) - exp (- slow * slow);
intensityFilter -> z [1] [i] *= factor;
intensityFilter -> z [2] [i] *= factor;
}
intensity.reset (Spectrum_to_Sound (intensityFilter.peek()));
n = intensity -> nx;
amp = intensity -> z [1];
for (long i = 1; i <= n; i ++) amp [i] = pow (10, amp [i] / 2);
/*
* Clip to maximum enhancement.
*/
ceiling = 1 + (maximumFactor - 1.0) * (0.5 - 0.5 * cos (NUMpi * fmid_bark / 13));
for (long i = 1; i <= n; i ++) amp [i] = 1 / (1 / amp [i] + 1 / ceiling);
n = thy nx;
amp = thy z [channel];
for (long i = 1; i <= n; i ++) amp [i] += band -> z [1] [i] * intensity -> z [1] [i];
fmin = fmax;
}
}
Vector_scale (thee.peek(), 0.99);
/* Truncate. */
thy xmin = my xmin;
thy xmax = my xmax;
thy nx = my nx;
thy x1 = my x1;
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, U": band modulation not deepened.");
}
}