double VocalTract_and_LPC_Frame_getMatchingLength (VocalTract me, LPC_Frame thee, double glottalDamping, bool radiationDamping, bool internalDamping) {
try {
// match the average distance between the first two formants in the VocaTract and the LPC spectrum
long numberOfFrequencies = 1000;
double maximumFrequency = 5000.0;
autoSpectrum vts = VocalTract_to_Spectrum (me, numberOfFrequencies, maximumFrequency, glottalDamping, radiationDamping, internalDamping);
double samplingFrequency = 1000.0 * my nx;
autoSpectrum lps = Spectrum_create (0.5 * samplingFrequency, numberOfFrequencies);
LPC_Frame_into_Spectrum (thee, lps.peek(), 0, 50);
autoSpectrumTier vtst = Spectrum_to_SpectrumTier_peaks (vts.peek());
autoSpectrumTier lpst = Spectrum_to_SpectrumTier_peaks (lps.peek());
double vt_f1 = vtst -> points.at [1] -> number, vt_f2 = vtst -> points.at [2] -> number;
double lp_f1 = lpst -> points.at [1] -> number, lp_f2 = lpst -> points.at [2] -> number;
double df1 = lp_f1 - vt_f1, df2 = lp_f2 - vt_f2, df = 0.5 * (df1 + df2);
double dl = - df / lp_f2;
return my dx * my nx * (1 + dl);
} catch (MelderError) {
Melder_throw (U"Length could not be determined from VocalTract and LPC_Frame.");
}
}
Spectrum LPC_to_Spectrum (LPC me, double t, double dfMin, double bandwidthReduction, double deEmphasisFrequency) {
try {
double samplingFrequency = 1.0 / my samplingPeriod;
long nfft = 2, index = Sampled_xToNearestIndex (me, t);
if (index < 1) {
index = 1;
}
if (index > my nx) {
index = my nx;
}
if (dfMin <= 0) {
nfft = 512; dfMin = samplingFrequency / nfft;
}
while (samplingFrequency / nfft > dfMin || nfft <= my d_frames[index].nCoefficients) {
nfft *= 2;
}
autoSpectrum thee = Spectrum_create (samplingFrequency / 2, nfft / 2 + 1);
LPC_Frame_into_Spectrum (& my d_frames[index], thee.peek(), bandwidthReduction, deEmphasisFrequency);
return thee.transfer();
} catch (MelderError) {
Melder_throw (me, ": no Spectrum created.");
}
}
