//-----------------------------------------------------------------------------
// SmoothingWithRecovery() carries out the spectral smoothing and spectral
// recovery on the Cepstrum domain.
//-----------------------------------------------------------------------------
void SmoothingWithRecovery(double f0, int fs, ForwardRealFFT forwardRealFFT, InverseRealFFT inverseRealFFT, double[] spectralEnvelope)
{
var smoothingLifter = new double[FFTSize];
var compensationLifter = new double[FFTSize];
smoothingLifter[0] = 1;
compensationLifter[0] = (1.0 - 2.0 * Q1) + 2.0 * Q1;
for (int i = 1, limit = forwardRealFFT.FFTSize / 2; i <= limit; i++)
{
var quefrency = (double)i / fs;
smoothingLifter[i] = Math.Sin(Math.PI * f0 * quefrency) / (Math.PI * f0 * quefrency);
compensationLifter[i] = (1.0 - 2.0 * Q1) + 2.0 * Q1 * Math.Cos(2.0 * Math.PI * quefrency * f0);
}
for (int i = 0, limit = FFTSize / 2; i <= limit; i++)
{
forwardRealFFT.Waveform[i] = Math.Log(forwardRealFFT.Waveform[i]);
}
for (int i = 1, limit = FFTSize / 2; i < limit; i++)
{
forwardRealFFT.Waveform[FFTSize - i] = forwardRealFFT.Waveform[i];
}
FFT.Execute(forwardRealFFT.ForwardFFT);
for (int i = 0, limit = FFTSize / 2; i <= limit; i++)
{
inverseRealFFT.Spectrum[i] = new Complex(forwardRealFFT.Spectrum[i].Real * smoothingLifter[i] * compensationLifter[i] / FFTSize, 0.0);
}
FFT.Execute(inverseRealFFT.InverseFFT);
for (int i = 0, limit = FFTSize / 2; i <= limit; i++)
{
spectralEnvelope[i] = Math.Exp(inverseRealFFT.Waveform[i]);
}
}
public void Synthesize(double[] f0, int f0Length, double[][] spectrogram, double[][] aperiodicity, int fftSize, double framePeriod, int fs, double[] y)
{
var minimumPhase = MinimumPhaseAnalysis.Create(fftSize);
var inverseRealFFT = InverseRealFFT.Create(fftSize);
var forwardRealFFT = ForwardRealFFT.Create(fftSize);
var pulseLocations = new double[y.Length];
var pulseLocationsIndex = new int[y.Length];
var pulseLocationsTimeShift = new double[y.Length];
var interpolatedVUV = new double[y.Length];
var numberOfPulses = GetTimeBase(f0, f0Length, fs, framePeriod / 1000.0, y.Length, fs / fftSize + 1.0, pulseLocations, pulseLocationsIndex, pulseLocationsTimeShift, interpolatedVUV);
var dcRemover = GetDCRemover(fftSize);
framePeriod /= 1000.0;
var impulseResponse = new double[fftSize];
for (var i = 0; i < numberOfPulses; i++)
{
var noiseSize = pulseLocationsIndex[Math.Min(numberOfPulses - 1, i + 1)] - pulseLocationsIndex[i];
GetOneFrameSegment(interpolatedVUV[pulseLocationsIndex[i]], noiseSize, spectrogram, fftSize, aperiodicity, f0Length, framePeriod, pulseLocations[i], pulseLocationsTimeShift[i], fs, forwardRealFFT, inverseRealFFT, minimumPhase, dcRemover, impulseResponse);
for (var j = 0; j < fftSize; j++)
{
var index = j + pulseLocationsIndex[i] - fftSize / 2 + 1;
if (index < 0 || index > y.Length - 1)
{
continue;
}
y[index] += impulseResponse[j];
}
}
}
public void Estimate(double[] x, int fs, double[] temporalPositions, double[] f0, int f0Length, int fftSize, double[][] aperiodicity)
{
aperiodicity.ForEach((a) => a.Fill(1.0 - SafeGuardMinimum));
var fftSizeD4C = (int)Math.Pow(2.0, 1.0 + (int)MathUtil.Log2(4.0 * fs / FloorF0D4C + 1.0));
var forwardRealFFT = ForwardRealFFT.Create(fftSizeD4C);
var numberOfAperiodicities = (int)(Math.Min(UpperLimit, fs / 2.0 - FrequencyInterval) / FrequencyInterval);
// Since the window function is common in D4CGeneralBody(),
// it is designed here to speed up.
var windowLength = (int)(FrequencyInterval * fftSizeD4C / fs) * 2 + 1;
var window = new double[windowLength];
Common.NuttallWindow(windowLength, window);
// D4C Love Train (Aperiodicity of 0 Hz is given by the different algorithm)
var aperiodicity0 = new double[f0Length];
D4CLoveTrain(x, fs, f0, f0Length, temporalPositions, aperiodicity0);
var coarseAperiodicity = new double[numberOfAperiodicities + 2];
coarseAperiodicity[0] = -60.0;
coarseAperiodicity[numberOfAperiodicities + 1] = -SafeGuardMinimum;
var coarseFrequencyAxis = Enumerable.Range(0, numberOfAperiodicities + 2).Select((i) => i * FrequencyInterval).ToArray();
coarseFrequencyAxis[numberOfAperiodicities + 1] = fs / 2.0;
var frequencyAxis = Enumerable.Range(0, fftSize / 2 + 1).Select((i) => (double)i * fs / fftSize).ToArray();
for (var i = 0; i < f0Length; i++)
{
if (f0[i] == 0.0 || aperiodicity0[i] <= Threshold)
{
continue;
}
D4CGeneralBody(x, fs, Math.Max(FloorF0D4C, f0[i]), fftSizeD4C, temporalPositions[i], numberOfAperiodicities, window, forwardRealFFT, coarseAperiodicity.SubSequence(1));
// Linear interpolation to convert the coarse aperiodicity into its
// spectral representation.
GetAperiodicity(coarseFrequencyAxis, coarseAperiodicity, numberOfAperiodicities, frequencyAxis, fftSize, aperiodicity[i]);
}
}
void GetNoiseSpectrum(int noiseSize, int fftSize, ForwardRealFFT forwardRealFFT)
{
var waveform = forwardRealFFT.Waveform;
for (var i = 0; i < noiseSize; i++)
{
waveform[i] = Rand.Next();
}
var average = noiseSize > 0 ? waveform.Take(noiseSize).Average() : 1.0;
for (var i = 0; i < noiseSize; i++)
{
waveform[i] -= average;
}
Array.Clear(waveform, noiseSize, fftSize - noiseSize);
FFT.Execute(forwardRealFFT.ForwardFFT);
}
//-----------------------------------------------------------------------------
// GetPowerSpectrum() calculates the power_spectrum with DC correction.
// DC stands for Direct Current. In this case, the component from 0 to F0 Hz
// is corrected.
//-----------------------------------------------------------------------------
void GetPowerSpectrum(int fs, double f0, ForwardRealFFT forwardRealFFT)
{
var halfWindowLength = MatlabFunctions.MatlabRound(1.5 * fs / f0);
// FFT
Array.Clear(forwardRealFFT.Waveform, halfWindowLength * 2 + 1, FFTSize - halfWindowLength * 2 - 1);
FFT.Execute(forwardRealFFT.ForwardFFT);
var powerSpectrum = forwardRealFFT.Waveform;
var spectrum = forwardRealFFT.Spectrum;
for (int i = 0, limit = FFTSize / 2; i <= limit; i++)
{
powerSpectrum[i] = spectrum[i].Real * spectrum[i].Real + spectrum[i].Imaginary * spectrum[i].Imaginary;
}
Common.DCCorrection(powerSpectrum, f0, fs, FFTSize, powerSpectrum);
}
public SynthesisRealTime(int sampleRate, double framePeriod, int fftSize, int bufferSize, int ringBufferCapacity)
{
SampleRate = sampleRate;
FramePeriod = framePeriod * 0.001;
AudioBufferSize = bufferSize;
AudioBuffer = new double[bufferSize * 2 + fftSize];
Buffer = new RingBuffer(ringBufferCapacity);
FFTSize = fftSize;
ImpulseResponse = new double[fftSize];
DCRemover = GetDCRemover(fftSize / 2);
RefreshSynthesizer();
MinimumPhase = MinimumPhaseAnalysis.Create(fftSize);
InverseRealFFT = InverseRealFFT.Create(fftSize);
ForwardRealFFT = ForwardRealFFT.Create(fftSize);
}
public void Estimate(double[] x, int fs, double[] temporalPositions, double[] f0, double[][] spectrogram)
{
var f0Floor = GetF0FloorForCheapTrick(fs, FFTSize);
var spectralEnvelope = new double[FFTSize];
var forwardRealFFT = ForwardRealFFT.Create(FFTSize);
var inverseRealFFT = InverseRealFFT.Create(FFTSize);
for (var i = 0; i < f0.Length; i++)
{
var currentF0 = f0[i] <= f0Floor ? DefaultF0 : f0[i];
CheapTrickGeneralBody(x, fs, currentF0, temporalPositions[i], forwardRealFFT, inverseRealFFT, spectralEnvelope);
for (int j = 0, limit = FFTSize / 2; j <= limit; j++)
{
spectrogram[i][j] = spectralEnvelope[j];
}
}
}
//-----------------------------------------------------------------------------
// D4CLoveTrain() determines the aperiodicity with VUV detection.
// If a frame was determined as the unvoiced section, aperiodicity is set to
// very high value as the safeguard.
// If it was voiced section, the aperiodicity of 0 Hz is set to -60 dB.
//-----------------------------------------------------------------------------
void D4CLoveTrain(double[] x, int fs, double[] f0, int f0Length, double[] temporalPositions, double[] aperiodicity0)
{
var lowestF0 = 40.0;
var fftSize = (int)Math.Pow(2.0, 1.0 + (int)MathUtil.Log2(3.0 * fs / lowestF0 + 1));
var forwardRealFFT = ForwardRealFFT.Create(fftSize);
// Cumulative powers at 100, 4000, 7900 Hz are used for VUV identification.
var boundary0 = (int)Math.Ceiling(100.0 * fftSize / fs);
var boundary1 = (int)Math.Ceiling(4000.0 * fftSize / fs);
var boundary2 = (int)Math.Ceiling(7900.0 * fftSize / fs);
for (var i = 0; i < f0Length; i++)
{
if (f0[i] == 0.0)
{
aperiodicity0[i] = 0.0;
continue;
}
aperiodicity0[i] = D4CLoveTrainSub(x, fs, Math.Max(f0[i], lowestF0), temporalPositions[i], f0Length, fftSize, boundary0, boundary1, boundary2, forwardRealFFT);
}
}
static void FastFFTFilt(double[] x, double[] h, int fftSize, ForwardRealFFT forwardRealFFT, InverseRealFFT inverseRealFFT, double[] y)
{
for (var i = 0; i < x.Length; i++)
{
forwardRealFFT.Waveform[i] = x[i] / fftSize;
}
if (x.Length < fftSize)
{
Array.Clear(forwardRealFFT.Waveform, x.Length, fftSize - x.Length);
}
FFT.Execute(forwardRealFFT.ForwardFFT);
var xSpectrum = new Complex[fftSize];
Array.Copy(forwardRealFFT.Spectrum, xSpectrum, fftSize / 2 + 1);
for (var i = 0; i < h.Length; i++)
{
forwardRealFFT.Waveform[i] = h[i] / fftSize;
}
if (h.Length < fftSize)
{
Array.Clear(forwardRealFFT.Waveform, h.Length, fftSize - h.Length);
}
FFT.Execute(forwardRealFFT.ForwardFFT);
for (var i = fftSize / 2 + 1; i > -1; i--)
{
inverseRealFFT.Spectrum[i] = new Complex(
xSpectrum[i].Real * forwardRealFFT.Spectrum[i].Real - xSpectrum[i].Imaginary * forwardRealFFT.Spectrum[i].Imaginary,
xSpectrum[i].Real * forwardRealFFT.Spectrum[i].Imaginary + xSpectrum[i].Imaginary * forwardRealFFT.Spectrum[i].Real
);
}
FFT.Execute(inverseRealFFT.InverseFFT);
inverseRealFFT.Waveform.BlockCopy(0, y, 0, fftSize);
}
//-----------------------------------------------------------------------------
// D4CGeneralBody() calculates a spectral envelope at a temporal
// position. This function is only used in D4C().
// Caution:
// forward_fft is allocated in advance to speed up the processing.
//-----------------------------------------------------------------------------
void D4CGeneralBody(double[] x, int fs, double currentF0, int fftSize, double currentPosition, int numberOfAperiodicities, double[] window, ForwardRealFFT forwardRealFFT, SubSequence <double> coarseAperiodicity)
{
var staticCentroid = new double[fftSize / 2 + 1];
var smoothedPowerSpectrum = new double[fftSize / 2 + 1];
var staticGroupDelay = new double[fftSize / 2 + 1];
GetStaticCentroid(x, fs, currentF0, fftSize, currentPosition, forwardRealFFT, staticCentroid);
GetSmoothedPowerSpectrum(x, fs, currentF0, fftSize, currentPosition, forwardRealFFT, smoothedPowerSpectrum);
GetStaticGroupDelay(staticCentroid, smoothedPowerSpectrum, fs, currentF0, fftSize, staticGroupDelay);
GetCoarseAperiodicity(staticGroupDelay, fs, fftSize, numberOfAperiodicities, window, forwardRealFFT, coarseAperiodicity);
// Revision of the result based on the F0
for (var i = 0; i < numberOfAperiodicities; i++)
{
coarseAperiodicity[i] = Math.Min(0.0, coarseAperiodicity[i] + (currentF0 - 100) / 50.0);
}
}
//-----------------------------------------------------------------------------
// GetSmoothedPowerSpectrum() calculates the smoothed power spectrum.
// The parameters used for smoothing are optimized in davance.
//-----------------------------------------------------------------------------
void GetSmoothedPowerSpectrum(double[] x, int fs, double currentF0, int fftSize, double currentPosition, ForwardRealFFT forwardRealFFT, double[] smoothedPowerSpectrum)
{
Array.Clear(forwardRealFFT.Waveform, 0, fftSize);
GetWindowedWaveform(x, fs, currentF0, currentPosition, WindowType.Hanning, 4.0, forwardRealFFT.Waveform);
FFT.Execute(forwardRealFFT.ForwardFFT);
var spectrum = forwardRealFFT.Spectrum;
for (int i = 0, limit = fftSize / 2; i <= limit; i++)
{
smoothedPowerSpectrum[i] = spectrum[i].Real * spectrum[i].Real + spectrum[i].Imaginary * spectrum[i].Imaginary;
}
Common.DCCorrection(smoothedPowerSpectrum, currentF0, fs, fftSize, smoothedPowerSpectrum);
Common.LinearSmoothing(smoothedPowerSpectrum, currentF0, fs, fftSize, smoothedPowerSpectrum);
}
//-----------------------------------------------------------------------------
// CheapTrickGeneralBody() calculates a spectral envelope at a temporal
// position. This function is only used in CheapTrick().
// Caution:
// forward_fft is allocated in advance to speed up the processing.
//-----------------------------------------------------------------------------
void CheapTrickGeneralBody(double[] x, int fs, double currentF0, double currentPosition, ForwardRealFFT forwardRealFFT, InverseRealFFT inverseRealFFT, double[] spectralEnvelope)
{
// F0-adaptive windowing
GetWindowedWaveform(x, fs, currentF0, currentPosition, forwardRealFFT);
// Calculate power spectrum with DC correction
// Note: The calculated power spectrum is stored in an array for waveform.
// In this imprementation, power spectrum is transformed by FFT (NOT IFFT).
// However, the same result is obtained.
// This is tricky but important for simple implementation.
GetPowerSpectrum(fs, currentF0, forwardRealFFT);
// Smoothing of the power (linear axis)
// forward_real_fft.waveform is the power spectrum.
Common.LinearSmoothing(forwardRealFFT.Waveform, currentF0 * 2.0 / 3.0, fs, FFTSize, forwardRealFFT.Waveform);
// Add infinitesimal noise
// This is a safeguard to avoid including zero in the spectrum.
AddInfinitesimalNoise(forwardRealFFT.Waveform, FFTSize, forwardRealFFT.Waveform);
// Smoothing (log axis) and spectral recovery on the cepstrum domain.
SmoothingWithRecovery(currentF0, fs, forwardRealFFT, inverseRealFFT, spectralEnvelope);
}
//-----------------------------------------------------------------------------
// GetStaticCentroid() calculates the temporally static energy centroid.
// Basic idea was proposed by H. Kawahara.
//-----------------------------------------------------------------------------
void GetStaticCentroid(double[] x, int fs, double currentF0, int fftSize, double currentPosition, ForwardRealFFT forwardRealFFT, double[] staticCentroid)
{
var centroid1 = new double[fftSize / 2 + 1];
var centroid2 = new double[fftSize / 2 + 1];
GetCentroid(x, fs, currentF0, fftSize, currentPosition - 0.25 / currentF0, forwardRealFFT, centroid1);
GetCentroid(x, fs, currentF0, fftSize, currentPosition + 0.25 / currentF0, forwardRealFFT, centroid2);
for (int i = 0, limit = fftSize / 2; i <= limit; i++)
{
staticCentroid[i] = centroid1[i] + centroid2[i];
}
Common.DCCorrection(staticCentroid, currentF0, fs, fftSize, staticCentroid);
}
//-----------------------------------------------------------------------------
// GetWindowedWaveform() windows the waveform by F0-adaptive window
//-----------------------------------------------------------------------------
void GetWindowedWaveform(double[] x, int fs, double currentF0, double currentPosition, ForwardRealFFT forwardRealFFT)
{
var halfWindowLength = MatlabFunctions.MatlabRound(1.5 * fs / currentF0);
var baseIndex = new int[halfWindowLength * 2 + 1];
var safeIndex = new int[halfWindowLength * 2 + 1];
var window = new double[halfWindowLength * 2 + 1];
SetParametersForGetWindowedWaveform(halfWindowLength, x.Length, currentPosition, fs, currentF0, baseIndex, safeIndex, window);
// F0-adaptive windowing
var waveForm = forwardRealFFT.Waveform;
for (int i = 0, limit = halfWindowLength * 2; i <= limit; i++)
{
waveForm[i] = x[safeIndex[i]] * window[i] + Rand.Next() * SafeGuardMinimum;
}
var tmpWeight1 = waveForm.Take(halfWindowLength * 2 + 1).Sum();
var tmpWeight2 = window.Sum();
var weightingCoefficient = tmpWeight1 / tmpWeight2;
for (int i = 0, limit = halfWindowLength * 2; i <= limit; i++)
{
waveForm[i] -= window[i] * weightingCoefficient;
}
}
void GetCentroid(double[] x, int fs, double currentF0, int fftSize, double currentPosition, ForwardRealFFT forwardRealFFT, double[] centroid)
{
Array.Clear(forwardRealFFT.Waveform, 0, fftSize);
GetWindowedWaveform(x, fs, currentF0, currentPosition, WindowType.Blackman, 4.0, forwardRealFFT.Waveform);
var windowRange = MatlabFunctions.MatlabRound(2.0 * fs / currentF0) * 2;
var power = Math.Sqrt(forwardRealFFT.Waveform.Take(windowRange).Sum((w) => w * w));
for (var i = 0; i <= windowRange; i++)
{
forwardRealFFT.Waveform[i] /= power;
}
FFT.Execute(forwardRealFFT.ForwardFFT);
var tmpSpectrum = new Complex[fftSize / 2 + 1];
Array.Copy(forwardRealFFT.Spectrum, tmpSpectrum, tmpSpectrum.Length);
for (var i = 0; i < fftSize; i++)
{
forwardRealFFT.Waveform[i] *= i + 1.0;
}
FFT.Execute(forwardRealFFT.ForwardFFT);
var spectrum = forwardRealFFT.Spectrum;
for (int i = 0, limit = fftSize / 2; i <= limit; i++)
{
centroid[i] = spectrum[i].Real * tmpSpectrum[i].Real + spectrum[i].Imaginary * tmpSpectrum[i].Imaginary;
}
}
//-----------------------------------------------------------------------------
// GetAperiodicResponse() calculates an aperiodic response.
//-----------------------------------------------------------------------------
void GetAperiodicResponse(int noiseSize, int fftSize, double[] spectrum, double[] aperiodicRatio, double currentVUV, ForwardRealFFT forwardRealFFT, InverseRealFFT inverseRealFFT, MinimumPhaseAnalysis minimumPhase, double[] aperiodicResponse)
{
GetNoiseSpectrum(noiseSize, fftSize, forwardRealFFT);
var logSpectrum = minimumPhase.LogSpectrum;
if (currentVUV != 0.0)
{
for (int i = 0, limit = minimumPhase.FFTSize / 2; i <= limit; i++)
{
logSpectrum[i] = Math.Log(spectrum[i] * aperiodicRatio[i]) / 2.0;
}
}
else
{
for (int i = 0, limit = minimumPhase.FFTSize / 2; i <= limit; i++)
{
logSpectrum[i] = Math.Log(spectrum[i]) / 2.0;
}
}
Common.GetMinimumPhaseSpectrum(minimumPhase);
var minimumPhaseSpectrum = minimumPhase.MinimumPhaseSpectrum;
Array.Copy(minimumPhaseSpectrum, 0, inverseRealFFT.Spectrum, 0, fftSize / 2 + 1);
for (int i = 0, limit = fftSize / 2; i <= limit; i++)
{
var real = minimumPhaseSpectrum[i].Real * forwardRealFFT.Spectrum[i].Real - minimumPhaseSpectrum[i].Imaginary * forwardRealFFT.Spectrum[i].Imaginary;
var imaginary = minimumPhaseSpectrum[i].Real * forwardRealFFT.Spectrum[i].Imaginary + minimumPhaseSpectrum[i].Imaginary * forwardRealFFT.Spectrum[i].Real;
inverseRealFFT.Spectrum[i] = new Complex(real, imaginary);
}
FFT.Execute(inverseRealFFT.InverseFFT);
MatlabFunctions.FFTShift(inverseRealFFT.Waveform.SubSequence(0, fftSize), aperiodicResponse);
}
double D4CLoveTrainSub(double[] x, int fs, double currentF0, double currentPosition, int f0Length, int fftSize, int boundary0, int boundary1, int boundary2, ForwardRealFFT forwardRealFFT)
{
var powerSpectrum = new double[fftSize];
var windowLength = MatlabFunctions.MatlabRound(1.5 * fs / currentF0) * 2 + 1;
GetWindowedWaveform(x, fs, currentF0, currentPosition, WindowType.Blackman, 3.0, forwardRealFFT.Waveform);
Array.Clear(forwardRealFFT.Waveform, windowLength, fftSize - windowLength);
FFT.Execute(forwardRealFFT.ForwardFFT);
var spectrum = forwardRealFFT.Spectrum;
for (int i = boundary0 + 1, limit = fftSize / 2 + 1; i < limit; i++)
{
powerSpectrum[i] = spectrum[i].Real * spectrum[i].Real + spectrum[i].Imaginary * spectrum[i].Imaginary;
}
for (var i = boundary0; i <= boundary2; i++)
{
powerSpectrum[i] += powerSpectrum[i - 1];
}
return(powerSpectrum[boundary1] / powerSpectrum[boundary2]);
}
//-----------------------------------------------------------------------------
// GetOneFrameSegment() calculates a periodic and aperiodic response at a time.
//-----------------------------------------------------------------------------
void GetOneFrameSegment(double currentVUV, int noiseSize, double[][] spectrogram, int fftSize, double[][] aperiodicity, int f0Length, double framePeriod, double currentTime, double fractionalTimeShift, int fs, ForwardRealFFT forwardRealFFT, InverseRealFFT inverseRealFFT, MinimumPhaseAnalysis minimumPhase, double[] dcRemover, double[] response)
{
var aperiodicResponse = new double[fftSize];
var periodicResponse = new double[fftSize];
var spectralEnvelope = new double[fftSize];
var aperiodicRatio = new double[fftSize];
GetSpectralEnvelope(currentTime, framePeriod, f0Length, spectrogram, fftSize, spectralEnvelope);
GetAperiodicRatio(currentTime, framePeriod, f0Length, aperiodicity, fftSize, aperiodicRatio);
// Synthesis of the periodic response
GetPeriodicResponse(fftSize, spectralEnvelope, aperiodicRatio, currentVUV, inverseRealFFT, minimumPhase, dcRemover, fractionalTimeShift, fs, periodicResponse);
// Synthesis of the aperiodic response
GetAperiodicResponse(noiseSize, fftSize, spectralEnvelope, aperiodicRatio, currentVUV, forwardRealFFT, inverseRealFFT, minimumPhase, aperiodicResponse);
var sqrtNoiseSize = Math.Sqrt(noiseSize);
for (var i = 0; i < fftSize; i++)
{
response[i] = (periodicResponse[i] * sqrtNoiseSize + aperiodicResponse[i]) / fftSize;
}
}
//-----------------------------------------------------------------------------
// GetCoarseAperiodicity() calculates the aperiodicity in multiples of 3 kHz.
// The upper limit is given based on the sampling frequency.
//-----------------------------------------------------------------------------
private void GetCoarseAperiodicity(double[] staticGroupDelay, int fs, int fftSize, int numberOfAperiodicities, double[] window, ForwardRealFFT forwardRealFFT, SubSequence <double> coarseAperiodicity)
{
var boundary = MatlabFunctions.MatlabRound(fftSize * 8.0 / window.Length);
var halfWindowLength = window.Length / 2;
Array.Clear(forwardRealFFT.Waveform, 0, fftSize);
var powerSpectrum = new double[fftSize / 2 + 1];
for (var i = 0; i < numberOfAperiodicities; i++)
{
var center = (int)(FrequencyInterval * (i + 1) * fftSize / fs);
for (int j = 0, limit = halfWindowLength * 2; j <= limit; j++)
{
forwardRealFFT.Waveform[j] = staticGroupDelay[center - halfWindowLength + j] * window[j];
}
FFT.Execute(forwardRealFFT.ForwardFFT);
var spectrum = forwardRealFFT.Spectrum;
for (int j = 0, limit = fftSize / 2; j <= limit; j++)
{
powerSpectrum[j] = spectrum[j].Real * spectrum[j].Real + spectrum[j].Imaginary * spectrum[j].Imaginary;
}
Array.Sort(powerSpectrum);
for (int j = 1, limit = fftSize / 2; j <= limit; j++)
{
powerSpectrum[j] += powerSpectrum[j - 1];
}
coarseAperiodicity[i] = 10.0 * Math.Log10(powerSpectrum[fftSize / 2 - boundary - 1] / powerSpectrum[fftSize / 2]);
}
}
