static LPC _Sound_to_LPC (Sound me, int predictionOrder, double analysisWidth, double dt,
double preEmphasisFrequency, int method, double tol1, double tol2) {
double t1, samplingFrequency = 1.0 / my dx;
double windowDuration = 2 * analysisWidth; /* gaussian window */
long nFrames, frameErrorCount = 0;
if (floor (windowDuration / my dx) < predictionOrder + 1) Melder_throw ("Analysis window duration too short.\n"
"For a prediction order of ", predictionOrder, " the analysis window duration has to be greater than ", my dx * (predictionOrder + 1),
"Please increase the analysis window duration or lower the prediction order.");
// Convenience: analyse the whole sound into one LPC_frame
if (windowDuration > my dx * my nx) {
windowDuration = my dx * my nx;
}
Sampled_shortTermAnalysis (me, windowDuration, dt, & nFrames, & t1);
autoSound sound = Data_copy (me);
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
autoLPC thee = LPC_create (my xmin, my xmax, nFrames, dt, t1, predictionOrder, my dx);
autoMelderProgress progress (L"LPC analysis");
if (preEmphasisFrequency < samplingFrequency / 2) {
Sound_preEmphasis (sound.peek(), preEmphasisFrequency);
}
for (long i = 1; i <= nFrames; i++) {
LPC_Frame lpcframe = (LPC_Frame) & thy d_frames[i];
double t = Sampled_indexToX (thee.peek(), i);
LPC_Frame_init (lpcframe, predictionOrder);
Sound_into_Sound (sound.peek(), sframe.peek(), t - windowDuration / 2);
Vector_subtractMean (sframe.peek());
Sounds_multiply (sframe.peek(), window.peek());
if (method == LPC_METHOD_AUTO) {
if (! Sound_into_LPC_Frame_auto (sframe.peek(), lpcframe)) {
frameErrorCount++;
}
} else if (method == LPC_METHOD_COVAR) {
if (! Sound_into_LPC_Frame_covar (sframe.peek(), lpcframe)) {
frameErrorCount++;
}
} else if (method == LPC_METHOD_BURG) {
if (! Sound_into_LPC_Frame_burg (sframe.peek(), lpcframe)) {
frameErrorCount++;
}
} else if (method == LPC_METHOD_MARPLE) {
if (! Sound_into_LPC_Frame_marple (sframe.peek(), lpcframe, tol1, tol2)) {
frameErrorCount++;
}
}
if ( (i % 10) == 1) {
Melder_progress ( (double) i / nFrames, L"LPC analysis of frame ",
Melder_integer (i), L" out of ", Melder_integer (nFrames), L".");
}
}
return thee.transfer();
}
autoBarkSpectrogram Sound_to_BarkSpectrogram (Sound me, double analysisWidth, double dt, double f1_bark, double fmax_bark, double df_bark) {
try {
double nyquist = 0.5 / my dx, samplingFrequency = 2 * nyquist;
double windowDuration = 2 * analysisWidth; /* gaussian window */
double zmax = NUMhertzToBark2 (nyquist);
double fmin_bark = 0;
// Check defaults.
if (f1_bark <= 0) {
f1_bark = 1;
}
if (fmax_bark <= 0) {
fmax_bark = zmax;
}
if (df_bark <= 0) {
df_bark = 1;
}
fmax_bark = MIN (fmax_bark, zmax);
long numberOfFilters = lround ( (fmax_bark - f1_bark) / df_bark);
if (numberOfFilters <= 0) {
Melder_throw (U"The combination of filter parameters is not valid.");
}
long numberOfFrames; double t1;
Sampled_shortTermAnalysis (me, windowDuration, dt, & numberOfFrames, & t1);
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
autoBarkSpectrogram thee = BarkSpectrogram_create (my xmin, my xmax, numberOfFrames, dt, t1, fmin_bark, fmax_bark, numberOfFilters, df_bark, f1_bark);
autoMelderProgress progess (U"BarkSpectrogram analysis");
for (long iframe = 1; iframe <= numberOfFrames; iframe++) {
double t = Sampled_indexToX (thee.get(), iframe);
Sound_into_Sound (me, sframe.get(), t - windowDuration / 2.0);
Sounds_multiply (sframe.get(), window.get());
Sound_into_BarkSpectrogram_frame (sframe.get(), thee.get(), iframe);
if (iframe % 10 == 1) {
Melder_progress ( (double) iframe / numberOfFrames, U"BarkSpectrogram analysis: frame ",
iframe, U" from ", numberOfFrames, U".");
}
}
_Spectrogram_windowCorrection ((Spectrogram) thee.get(), window -> nx);
return thee;
} catch (MelderError) {
Melder_throw (me, U": no BarkSpectrogram created.");
}
}
autoMelSpectrogram Sound_to_MelSpectrogram (Sound me, double analysisWidth, double dt, double f1_mel, double fmax_mel, double df_mel) {
try {
double t1, samplingFrequency = 1.0 / my dx, nyquist = 0.5 * samplingFrequency;
double windowDuration = 2.0 * analysisWidth; // gaussian window
double fmin_mel = 0.0;
double fbottom = NUMhertzToMel2 (100.0), fceiling = NUMhertzToMel2 (nyquist);
long numberOfFrames;
// Check defaults.
if (fmax_mel <= 0.0 || fmax_mel > fceiling) {
fmax_mel = fceiling;
}
if (fmax_mel <= f1_mel) {
f1_mel = fbottom; fmax_mel = fceiling;
}
if (f1_mel <= 0.0) {
f1_mel = fbottom;
}
if (df_mel <= 0.0) {
df_mel = 100.0;
}
// Determine the number of filters.
long numberOfFilters = lround ((fmax_mel - f1_mel) / df_mel);
fmax_mel = f1_mel + numberOfFilters * df_mel;
Sampled_shortTermAnalysis (me, windowDuration, dt, &numberOfFrames, &t1);
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
autoMelSpectrogram thee = MelSpectrogram_create (my xmin, my xmax, numberOfFrames, dt, t1, fmin_mel, fmax_mel, numberOfFilters, df_mel, f1_mel);
autoMelderProgress progress (U"MelSpectrograms analysis");
for (long iframe = 1; iframe <= numberOfFrames; iframe++) {
double t = Sampled_indexToX (thee.get(), iframe);
Sound_into_Sound (me, sframe.get(), t - windowDuration / 2.0);
Sounds_multiply (sframe.get(), window.get());
Sound_into_MelSpectrogram_frame (sframe.get(), thee.get(), iframe);
if (iframe % 10 == 1) {
Melder_progress ((double) iframe / numberOfFrames, U"Frame ", iframe, U" out of ", numberOfFrames, U".");
}
}
_Spectrogram_windowCorrection ((Spectrogram) thee.get(), window -> nx);
return thee;
} catch (MelderError) {
Melder_throw (me, U": no MelSpectrogram created.");
}
}
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.");
}
}
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.");
}
}
BarkFilter Sound_to_BarkFilter (Sound me, double analysisWidth, double dt,
double f1_bark, double fmax_bark, double df_bark) {
try {
double t1, nyquist = 0.5 / my dx, samplingFrequency = 2 * nyquist;
double windowDuration = 2 * analysisWidth; /* gaussian window */
double zmax = NUMhertzToBark2 (nyquist);
double fmin_bark = 0;
long nt, frameErrorCount = 0;
// Check defaults.
if (f1_bark <= 0) {
f1_bark = 1;
}
if (fmax_bark <= 0) {
fmax_bark = zmax;
}
if (df_bark <= 0) {
df_bark = 1;
}
fmax_bark = MIN (fmax_bark, zmax);
long nf = floor ( (fmax_bark - f1_bark) / df_bark + 0.5);
if (nf <= 0) {
Melder_throw ("The combination of filter parameters is not valid.");
}
Sampled_shortTermAnalysis (me, windowDuration, dt, & nt, & t1);
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
autoBarkFilter thee = BarkFilter_create (my xmin, my xmax, nt, dt, t1,
fmin_bark, fmax_bark, nf, df_bark, f1_bark);
autoMelderProgress progess (L"BarkFilter analysis");
for (long i = 1; i <= nt; i++) {
double t = Sampled_indexToX (thee.peek(), i);
Sound_into_Sound (me, sframe.peek(), t - windowDuration / 2);
Sounds_multiply (sframe.peek(), window.peek());
if (! Sound_into_BarkFilter_frame (sframe.peek(), thee.peek(), i)) {
frameErrorCount++;
}
if ( (i % 10) == 1) {
Melder_progress ( (double) i / nt, L"BarkFilter analysis: frame ",
Melder_integer (i), L" from ", Melder_integer (nt), L"."); therror
}
}
if (frameErrorCount > 0) {
Melder_warning (L"Analysis results of ", Melder_integer (frameErrorCount), L" frame(s) out of ",
Melder_integer (nt), L" will be suspect.");
}
double ref = FilterBank_DBREF * gaussian_window_squared_correction (window -> nx);
NUMdmatrix_to_dBs (thy z, 1, thy ny, 1, thy nx, ref, FilterBank_DBFAC, FilterBank_DBFLOOR);
return thee.transfer();
} catch (MelderError) {
FormantFilter Sound_and_Pitch_to_FormantFilter (Sound me, Pitch thee, double analysisWidth, double dt,
double f1_hz, double fmax_hz, double df_hz, double relative_bw) {
try {
double t1, windowDuration = 2 * analysisWidth; /* gaussian window */
double nyquist = 0.5 / my dx, samplingFrequency = 2 * nyquist, fmin_hz = 0;
long nt, f0_undefined = 0;
if (my xmin > thy xmin || my xmax > thy xmax) Melder_throw
("The domain of the Sound is not included in the domain of the Pitch.");
double f0_median = Pitch_getQuantile (thee, thy xmin, thy xmax, 0.5, kPitch_unit_HERTZ);
if (f0_median == NUMundefined || f0_median == 0) {
f0_median = 100;
Melder_warning (L"Pitch values undefined. Bandwith fixed to 100 Hz. ");
}
if (f1_hz <= 0) {
f1_hz = 100;
}
if (fmax_hz <= 0) {
fmax_hz = nyquist;
}
if (df_hz <= 0) {
df_hz = f0_median / 2;
}
if (relative_bw <= 0) {
relative_bw = 1.1;
}
fmax_hz = MIN (fmax_hz, nyquist);
long nf = floor ( (fmax_hz - f1_hz) / df_hz + 0.5);
Sampled_shortTermAnalysis (me, windowDuration, dt, &nt, &t1);
autoFormantFilter him = FormantFilter_create (my xmin, my xmax, nt, dt, t1,
fmin_hz, fmax_hz, nf, df_hz, f1_hz);
// Temporary objects
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
autoMelderProgress progress (L"Sound & Pitch: To FormantFilter");
for (long i = 1; i <= nt; i++) {
double t = Sampled_indexToX (him.peek(), i);
double b, f0 = Pitch_getValueAtTime (thee, t, kPitch_unit_HERTZ, 0);
if (f0 == NUMundefined || f0 == 0) {
f0_undefined++; f0 = f0_median;
}
b = relative_bw * f0;
Sound_into_Sound (me, sframe.peek(), t - windowDuration / 2);
Sounds_multiply (sframe.peek(), window.peek());
Sound_into_FormantFilter_frame (sframe.peek(), him.peek(), i, b);
if ( (i % 10) == 1) {
Melder_progress ( (double) i / nt, L"Frame ", Melder_integer (i), L" out of ",
Melder_integer (nt), L".");
}
}
double ref = FilterBank_DBREF * gaussian_window_squared_correction (window -> nx);
NUMdmatrix_to_dBs (his z, 1, his ny, 1, his nx, ref, FilterBank_DBFAC, FilterBank_DBFLOOR);
return him.transfer();
} catch (MelderError) {
Melder_throw ("FormantFilter not created from Pitch & FormantFilter.");
}
}
MelFilter Sound_to_MelFilter (Sound me, double analysisWidth, double dt,
double f1_mel, double fmax_mel, double df_mel) {
try {
double t1, samplingFrequency = 1 / my dx, nyquist = 0.5 * samplingFrequency;
double windowDuration = 2 * analysisWidth; /* gaussian window */
double fmin_mel = 0;
double fbottom = HZTOMEL (100.0), fceiling = HZTOMEL (nyquist);
long nt, frameErrorCount = 0;
// Check defaults.
if (fmax_mel <= 0 || fmax_mel > fceiling) {
fmax_mel = fceiling;
}
if (fmax_mel <= f1_mel) {
f1_mel = fbottom; fmax_mel = fceiling;
}
if (f1_mel <= 0) {
f1_mel = fbottom;
}
if (df_mel <= 0) {
df_mel = 100.0;
}
// Determine the number of filters.
long nf = floor ( (fmax_mel - f1_mel) / df_mel + 0.5);
fmax_mel = f1_mel + nf * df_mel;
Sampled_shortTermAnalysis (me, windowDuration, dt, &nt, &t1);
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
autoMelFilter thee = MelFilter_create (my xmin, my xmax, nt, dt, t1, fmin_mel,
fmax_mel, nf, df_mel, f1_mel);
autoMelderProgress progress (L"MelFilters analysis");
for (long i = 1; i <= nt; i++) {
double t = Sampled_indexToX (thee.peek(), i);
Sound_into_Sound (me, sframe.peek(), t - windowDuration / 2);
Sounds_multiply (sframe.peek(), window.peek());
if (! Sound_into_MelFilter_frame (sframe.peek(), thee.peek(), i)) {
frameErrorCount++;
}
if ( (i % 10) == 1) {
Melder_progress ( (double) i / nt, L"Frame ", Melder_integer (i), L" out of ",
Melder_integer (nt), L".");
}
}
if (frameErrorCount) Melder_warning (L"Analysis results of ", Melder_integer (frameErrorCount),
L" frame(s) out of ", Melder_integer (nt), L" will be suspect.");
// Window correction.
double ref = FilterBank_DBREF * gaussian_window_squared_correction (window -> nx);
NUMdmatrix_to_dBs (thy z, 1, thy ny, 1, thy nx, ref, FilterBank_DBFAC, FilterBank_DBFLOOR);
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": no MelFilter created.");
}
}
autoSpectrogram Sound_and_Pitch_to_Spectrogram (Sound me, Pitch thee, double analysisWidth, double dt, double f1_hz, double fmax_hz, double df_hz, double relative_bw) {
try {
double t1, windowDuration = 2.0 * analysisWidth; /* gaussian window */
double nyquist = 0.5 / my dx, samplingFrequency = 2.0 * nyquist, fmin_hz = 0.0;
long numberOfFrames, f0_undefined = 0.0;
if (my xmin > thy xmin || my xmax > thy xmax) Melder_throw
(U"The domain of the Sound is not included in the domain of the Pitch.");
double f0_median = Pitch_getQuantile (thee, thy xmin, thy xmax, 0.5, kPitch_unit_HERTZ);
if (f0_median == NUMundefined || f0_median == 0.0) {
f0_median = 100.0;
Melder_warning (U"Pitch values undefined. Bandwith fixed to 100 Hz. ");
}
if (f1_hz <= 0.0) {
f1_hz = 100.0;
}
if (fmax_hz <= 0.0) {
fmax_hz = nyquist;
}
if (df_hz <= 0.0) {
df_hz = f0_median / 2.0;
}
if (relative_bw <= 0.0) {
relative_bw = 1.1;
}
fmax_hz = MIN (fmax_hz, nyquist);
long numberOfFilters = lround ( (fmax_hz - f1_hz) / df_hz);
Sampled_shortTermAnalysis (me, windowDuration, dt, &numberOfFrames, &t1);
autoSpectrogram him = Spectrogram_create (my xmin, my xmax, numberOfFrames, dt, t1, fmin_hz, fmax_hz, numberOfFilters, df_hz, f1_hz);
// Temporary objects
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
autoMelderProgress progress (U"Sound & Pitch: To FormantFilter");
for (long iframe = 1; iframe <= numberOfFrames; iframe++) {
double t = Sampled_indexToX (him.get(), iframe);
double b, f0 = Pitch_getValueAtTime (thee, t, kPitch_unit_HERTZ, 0);
if (f0 == NUMundefined || f0 == 0.0) {
f0_undefined ++;
f0 = f0_median;
}
b = relative_bw * f0;
Sound_into_Sound (me, sframe.get(), t - windowDuration / 2.0);
Sounds_multiply (sframe.get(), window.get());
Sound_into_Spectrogram_frame (sframe.get(), him.get(), iframe, b);
if (iframe % 10 == 1) {
Melder_progress ( (double) iframe / numberOfFrames, U"Frame ", iframe, U" out of ",
numberOfFrames, U".");
}
}
_Spectrogram_windowCorrection (him.get(), window -> nx);
return him;
} catch (MelderError) {
Melder_throw (U"FormantFilter not created from Pitch & FormantFilter.");
}
}
SPINET Sound_to_SPINET (Sound me, double timeStep, double windowDuration,
double minimumFrequencyHz, double maximumFrequencyHz, long nFilters,
double excitationErbProportion, double inhibitionErbProportion)
{
Sound window = NULL, frame = NULL; SPINET thee = NULL;
long i, j, k, numberOfFrames;
double firstTime, b = 1.02, samplingFrequency = 1 / my dx;
double *f = NULL, *bw = NULL, *aex = NULL, *ain = NULL;
if (timeStep < my dx) timeStep = my dx;
if (maximumFrequencyHz > samplingFrequency / 2) maximumFrequencyHz = samplingFrequency / 2;
if (! Sampled_shortTermAnalysis (me, windowDuration, timeStep, &numberOfFrames, &firstTime) ||
! (thee = SPINET_create (my xmin, my xmax, numberOfFrames, timeStep, firstTime,
minimumFrequencyHz, maximumFrequencyHz, nFilters,
excitationErbProportion, inhibitionErbProportion)) ||
! (window = Sound_createGaussian (windowDuration, samplingFrequency)) ||
! (frame = Sound_createSimple (1, windowDuration, samplingFrequency)) ||
! (f = NUMdvector (1, nFilters)) || ! (bw = NUMdvector (1, nFilters)) ||
! (aex = NUMdvector (1, nFilters)) || ! (ain = NUMdvector (1, nFilters))) goto cleanup;
/*
Cochlear filterbank: gammatone
*/
for (i=1; i <= nFilters; i++)
{
f[i] = NUMerbToHertz (thy y1 + (i - 1) * thy dy);
bw[i] = 2 * NUMpi * b * (f[i] * (6.23e-6 * f[i] + 93.39e-3) + 28.52);
}
Melder_progress1 (0.0, L"SPINET analysis");
for (i=1; i <= nFilters; i++)
{
Sound gammaTone = NULL, filtered = NULL;
/* Contribution of outer & middle ear and phase locking */
double bb = (f[i] / 1000) * exp (- f[i] / 1000);
/* Time where gammafunction envelope has its maximum */
double tgammaMax = (thy gamma - 1) / bw[i];
/* Amplitude at tgammaMax */
double gammaMaxAmplitude = pow ((thy gamma - 1) / (NUMe * bw[i]), (thy gamma - 1));
double timeCorrection = tgammaMax - windowDuration / 2;
if (! (gammaTone = Sound_createGammaTone (0, 0.1, samplingFrequency,
thy gamma, b, f[i], 0, 0, 0)) ||
/* filtering can be made 30% faster by taking Spectrum(me) outside the loop */
! (filtered = Sounds_convolve (me, gammaTone, kSounds_convolve_scaling_SUM, kSounds_convolve_signalOutsideTimeDomain_ZERO))) { forget (gammaTone); goto cleanup; }
/*
To energy measure: weigh with broad-band transfer function
*/
for (j=1; j <= numberOfFrames; j++)
{
Sound_into_Sound (filtered, frame, Sampled_indexToX (thee, j) + timeCorrection);
Sounds_multiply (frame, window);
thy y[i][j] = Sound_power (frame) * bb / gammaMaxAmplitude;
}
forget (filtered); forget (gammaTone);
if (! Melder_progress5 ((double)i / nFilters, L"SPINET: filter ", Melder_integer (i), L" from ",
Melder_integer (nFilters), L".")) goto cleanup;
}
/*
Excitatory and inhibitory area functions
*/
for (i=1; i <= nFilters; i++)
{
for (k=1; k <= nFilters; k++)
{
double fr = (f[k] - f[i]) / bw[i];
aex[i] += fgamma (fr / thy excitationErbProportion, thy gamma);
ain[i] += fgamma (fr / thy inhibitionErbProportion, thy gamma);
}
}
/*
On-center off-surround interactions
*/
for (j=1; j <= numberOfFrames; j++)
for (i=1; i <= nFilters; i++)
{
double a = 0;
for (k=1; k <= nFilters; k++)
{
double fr = (f[k] - f[i]) / bw[i];
double hexsq = fgamma (fr / thy excitationErbProportion, thy gamma);
double hinsq = fgamma (fr / thy inhibitionErbProportion, thy gamma);
a += thy y[k][j] * (hexsq / aex[i] - hinsq / ain[i]);
}
thy s[i][j] = a > 0 ? a : 0;
}
Melder_progress1 (1.0, NULL);
cleanup:
NUMdvector_free (aex, 1); NUMdvector_free (ain, 1);
NUMdvector_free (f, 1); NUMdvector_free (bw, 1);
forget (window); forget (frame);
if (! Melder_hasError()) return thee;
forget (thee);
return Melder_errorp1 (L"Sound_to_SPINET: not performed.");
}
LPC LPC_and_Sound_to_LPC_robust (LPC thee, Sound me, double analysisWidth, double preEmphasisFrequency, double k,
int itermax, double tol, int wantlocation) {
struct huber_struct struct_huber = { 0 };
try {
double t1, samplingFrequency = 1.0 / my dx, tol_svd = 0.000001;
double location = 0, windowDuration = 2 * analysisWidth; /* Gaussian window */
long nFrames, frameErrorCount = 0, iter = 0;
long p = thy maxnCoefficients;
if (my xmin != thy xmin || my xmax != thy xmax) {
Melder_throw ("Time domains differ.");
}
if (my dx != thy samplingPeriod) {
Melder_throw ("Sampling intervals differ.");
}
if (floor (windowDuration / my dx) < p + 1) {
Melder_throw ("Analysis window too short.");
}
Sampled_shortTermAnalysis (me, windowDuration, thy dx, & nFrames, & t1);
if (nFrames != thy nx || t1 != thy x1) {
Melder_throw ("Incorrect retrieved analysis width");
}
autoSound sound = Data_copy (me);
autoSound sframe = Sound_createSimple (1, windowDuration, samplingFrequency);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
autoLPC him = Data_copy (thee);
huber_struct_init (&struct_huber, windowDuration, p, samplingFrequency, location, wantlocation);
struct_huber.k = k;
struct_huber.tol = tol;
struct_huber.tol_svd = tol_svd;
struct_huber.itermax = itermax;
autoMelderProgress progess (L"LPC analysis");
Sound_preEmphasis (sound.peek(), preEmphasisFrequency);
for (long i = 1; i <= nFrames; i++) {
LPC_Frame lpc = (LPC_Frame) & thy d_frames[i];
LPC_Frame lpcto = (LPC_Frame) & his d_frames[i];
double t = Sampled_indexToX (thee, i);
Sound_into_Sound (sound.peek(), sframe.peek(), t - windowDuration / 2);
Vector_subtractMean (sframe.peek());
Sounds_multiply (sframe.peek(), window.peek());
try {
LPC_Frames_and_Sound_huber (lpc, sframe.peek(), lpcto, & struct_huber);
} catch (MelderError) {
frameErrorCount++;
}
iter += struct_huber.iter;
if ( (i % 10) == 1) {
Melder_progress ( (double) i / nFrames, L"LPC analysis of frame ",
Melder_integer (i), L" out of ", Melder_integer (nFrames), L".");
}
}
if (frameErrorCount) Melder_warning (L"Results of ", Melder_integer (frameErrorCount),
L" frame(s) out of ", Melder_integer (nFrames), L" could not be optimised.");
MelderInfo_writeLine4 (L"Number of iterations: ", Melder_integer (iter),
L"\n Average per frame: ", Melder_double (((double) iter) / nFrames));
huber_struct_destroy (&struct_huber);
return him.transfer();
} catch (MelderError) {
huber_struct_destroy (&struct_huber);
Melder_throw (me, ": no robust LPC created.");
}
}
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.");
}
}
SPINET Sound_to_SPINET (Sound me, double timeStep, double windowDuration,
double minimumFrequencyHz, double maximumFrequencyHz, long nFilters,
double excitationErbProportion, double inhibitionErbProportion) {
try {
double firstTime, b = 1.02, samplingFrequency = 1 / my dx;
if (timeStep < my dx) {
timeStep = my dx;
}
if (maximumFrequencyHz > samplingFrequency / 2) {
maximumFrequencyHz = samplingFrequency / 2;
}
long numberOfFrames;
Sampled_shortTermAnalysis (me, windowDuration, timeStep, &numberOfFrames, &firstTime);
autoSPINET thee = SPINET_create (my xmin, my xmax, numberOfFrames, timeStep, firstTime,
minimumFrequencyHz, maximumFrequencyHz, nFilters, excitationErbProportion, inhibitionErbProportion);
autoSound window = Sound_createGaussian (windowDuration, samplingFrequency);
autoSound frame = Sound_createSimple (1, windowDuration, samplingFrequency);
autoNUMvector<double> f (1, nFilters);
autoNUMvector<double> bw (1, nFilters);
autoNUMvector<double> aex (1, nFilters);
autoNUMvector<double> ain (1, nFilters);
// Cochlear filterbank: gammatone
for (long i = 1; i <= nFilters; i++) {
f[i] = NUMerbToHertz (thy y1 + (i - 1) * thy dy);
bw[i] = 2 * NUMpi * b * (f[i] * (6.23e-6 * f[i] + 93.39e-3) + 28.52);
}
autoMelderProgress progress (L"SPINET analysis");
for (long i = 1; i <= nFilters; i++) {
double bb = (f[i] / 1000) * exp (- f[i] / 1000); // outer & middle ear and phase locking
double tgammaMax = (thy gamma - 1) / bw[i]; // Time where gammafunction envelope has maximum
double gammaMaxAmplitude = pow ( (thy gamma - 1) / (NUMe * bw[i]), (thy gamma - 1)); // tgammaMax
double timeCorrection = tgammaMax - windowDuration / 2;
autoSound gammaTone = Sound_createGammaTone (0, 0.1, samplingFrequency,
thy gamma, b, f[i], 0, 0, 0);
autoSound filtered = Sounds_convolve (me, gammaTone.peek(), kSounds_convolve_scaling_SUM, kSounds_convolve_signalOutsideTimeDomain_ZERO);
// To energy measure: weigh with broad-band transfer function
for (long j = 1; j <= numberOfFrames; j++) {
Sound_into_Sound (filtered.peek(), frame.peek(), Sampled_indexToX (thee.peek(), j) + timeCorrection);
Sounds_multiply (frame.peek(), window.peek());
thy y[i][j] = Sound_power (frame.peek()) * bb / gammaMaxAmplitude;
}
Melder_progress ( (double) i / nFilters, L"SPINET: filter ", Melder_integer (i), L" from ",
Melder_integer (nFilters), L".");
}
// Excitatory and inhibitory area functions
for (long i = 1; i <= nFilters; i++) {
for (long k = 1; k <= nFilters; k++) {
double fr = (f[k] - f[i]) / bw[i];
aex[i] += fgamma (fr / thy excitationErbProportion, thy gamma);
ain[i] += fgamma (fr / thy inhibitionErbProportion, thy gamma);
}
}
// On-center off-surround interactions
for (long j = 1; j <= numberOfFrames; j++)
for (long i = 1; i <= nFilters; i++) {
double a = 0;
for (long k = 1; k <= nFilters; k++) {
double fr = (f[k] - f[i]) / bw[i];
double hexsq = fgamma (fr / thy excitationErbProportion, thy gamma);
double hinsq = fgamma (fr / thy inhibitionErbProportion, thy gamma);
a += thy y[k][j] * (hexsq / aex[i] - hinsq / ain[i]);
}
thy s[i][j] = a > 0 ? a : 0;
}
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": no SPINET created.");
}
}
