/// <summary>
/// Fast convolution via FFT for arrays of samples (maximally in-place).
/// This version is best suited for block processing when memory needs to be reused.
/// Input arrays must have size equal to the size of FFT.
/// </summary>
/// <param name="real1">Real parts of the 1st signal (zero-padded)</param>
/// <param name="imag1">Imaginary parts of the 1st signal (zero-padded)</param>
/// <param name="real2">Real parts of the 2nd signal (zero-padded)</param>
/// <param name="imag2">Imaginary parts of the 2nd signal (zero-padded)</param>
/// <param name="res">Real parts of resulting convolution (zero-padded if center == 0)</param>
/// <param name="center">
/// Position of central sample for the case of 2*M-1 convolution
/// (if it is set then resulting array has length of M)
/// </param>
public static void Convolve(float[] real1, float[] imag1, float[] real2, float[] imag2, float[] res, int center = 0)
{
var fftSize = real1.Length;
var fft = new Fft(fftSize);
// 1) do FFT of both signals
fft.Direct(real1, imag1);
fft.Direct(real2, imag2);
// 2) do complex multiplication of spectra and normalize
for (var i = 0; i < fftSize; i++)
{
var re = real1[i] * real2[i] - imag1[i] * imag2[i];
var im = real1[i] * imag2[i] + imag1[i] * real2[i];
real1[i] = re / fftSize;
imag1[i] = im / fftSize;
}
// 3) do inverse FFT of resulting spectrum
fft.Inverse(real1, imag1);
// 4) return output array
if (center > 0)
{
real1.FastCopyTo(res, center, center - 1);
}
else
{
real1.FastCopyTo(res, fftSize);
}
}
/// <summary>
/// Estimate noise power spectrum
/// </summary>
/// <param name="noise"></param>
private void EstimateNoise(DiscreteSignal noise)
{
var numFrames = 0;
for (var pos = 0; pos + _fftSize < noise.Length; pos += _hopSize, numFrames++)
{
noise.Samples.FastCopyTo(_re, _fftSize, pos);
_zeroblock.FastCopyTo(_im, _fftSize);
_fft.Direct(_re, _im);
for (var j = 0; j <= _fftSize / 2; j++)
{
_noiseAcc[j] += _re[j] * _re[j] + _im[j] * _im[j];
}
}
// (including smoothing)
for (var j = 1; j < _fftSize / 2; j++)
{
_noiseEstimate[j] = (_noiseAcc[j - 1] + _noiseAcc[j] + _noiseAcc[j + 1]) / (3 * numFrames);
}
_noiseEstimate[0] /= numFrames;
_noiseEstimate[_fftSize / 2] /= numFrames;
}
/// <summary>
/// Fast convolution via FFT for arrays of samples (maximally in-place).
/// This version is best suited for block processing when memory needs to be reused.
/// Input arrays must have size equal to the size of FFT.
/// FFT size MUST be set properly in constructor!
/// </summary>
/// <param name="input">Real parts of the 1st signal (zero-padded)</param>
/// <param name="kernel">Real parts of the 2nd signal (zero-padded)</param>
/// <param name="output">Real parts of resulting convolution (zero-padded)</param>
public void Convolve(float[] input, float[] kernel, float[] output)
{
_zeroblock.FastCopyTo(_real1, _fftSize);
_zeroblock.FastCopyTo(_real2, _fftSize);
_zeroblock.FastCopyTo(_imag1, _fftSize);
_zeroblock.FastCopyTo(_imag2, _fftSize);
input.FastCopyTo(_real1, input.Length);
kernel.FastCopyTo(_real2, kernel.Length);
// 1) do FFT of both signals
_fft.Direct(_real1, _imag1);
_fft.Direct(_real2, _imag2);
// 2) do complex multiplication of spectra and normalize
for (var i = 0; i < _fftSize; i++)
{
var re = _real1[i] * _real2[i] - _imag1[i] * _imag2[i];
var im = _real1[i] * _imag2[i] + _imag1[i] * _real2[i];
output[i] = re / _fftSize;
_imag1[i] = im / _fftSize;
}
// 3) do inverse FFT of resulting spectrum
_fft.Inverse(output, _imag1);
}
/// <summary>
/// Process one frame (block)
/// </summary>
public void ProcessFrame()
{
_zeroblock.FastCopyTo(_im1, _fftSize);
_zeroblock.FastCopyTo(_im2, _fftSize);
_dl1.FastCopyTo(_re1, _fftSize);
_dl2.FastCopyTo(_re2, _fftSize);
_re1.ApplyWindow(_window);
_re2.ApplyWindow(_window);
_fft.Direct(_re1, _im1);
_fft.Direct(_re2, _im2);
for (var j = 0; j <= _fftSize / 2; j++)
{
var mag1 = Math.Sqrt(_re1[j] * _re1[j] + _im1[j] * _im1[j]);
var phase2 = Math.Atan2(_im2[j], _re2[j]);
_filteredRe[j] = (float)(mag1 * Math.Cos(phase2));
_filteredIm[j] = (float)(mag1 * Math.Sin(phase2));
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
_filteredRe[j] = _filteredIm[j] = 0.0f;
}
_fft.Inverse(_filteredRe, _filteredIm);
_filteredRe.ApplyWindow(_window);
for (var j = 0; j < _overlapSize; j++)
{
_filteredRe[j] += _lastSaved[j];
}
_filteredRe.FastCopyTo(_lastSaved, _overlapSize, _hopSize);
for (var i = 0; i < _filteredRe.Length; i++) // Wet / Dry mix
{
_filteredRe[i] *= Wet / _fftSize;
_filteredRe[i] += _dl2[i] * Dry;
}
_dl1.FastCopyTo(_dl1, _overlapSize, _hopSize);
_dl2.FastCopyTo(_dl2, _overlapSize, _hopSize);
_inOffset = _overlapSize;
_outOffset = 0;
}
// Update chart of frequency domain
private void UpdateSpectra()
{
var fftSize = int.Parse(fftSizeTextBox.Text);
var cepstrumSize = int.Parse(cepstrumSizeTextBox.Text);
_hopSize = int.Parse(hopSizeTextBox.Text);
if (fftSize != _fftSize)
{
_fftSize = fftSize;
_fft = new Fft(fftSize);
_cepstralTransform = new CepstralTransform(cepstrumSize, _fftSize);
}
if (cepstrumSize != _cepstrumSize)
{
_cepstrumSize = cepstrumSize;
_cepstralTransform = new CepstralTransform(_cepstrumSize, _fftSize);
}
var pos = _hopSize * _specNo;
var block = _signal[pos, pos + _fftSize];
block.ApplyWindow(WindowTypes.Hamming);
var cepstrum = _cepstralTransform.Direct(block);
var real = new float[_fftSize];
var imag = new float[_fftSize];
for (var i = 0; i < 32; i++)
{
real[i] = cepstrum[i];
}
_fft.Direct(real, imag);
var spectrum = _fft.PowerSpectrum(block, normalize: false).Samples;
var avg = spectrum.Average(s => LevelScale.ToDecibel(s));
var spectrumEstimate = real.Take(_fftSize / 2 + 1)
.Select(s => (float)LevelScale.FromDecibel(s * 40 / _fftSize - avg))
.ToArray();
spectrumPanel.Line = spectrum;
spectrumPanel.Markline = spectrumEstimate;
spectrumPanel.ToDecibel();
spectrumPanel.max_freq_value = spectrum.Length * _signal.SamplingRate / fftSize;
}
public void ComplexFftArray()
{
var reInput = new float[FrameSize];
var imInput = new float[FrameSize];
var re = new float[FrameSize];
var im = new float[FrameSize];
for (var i = 0; i < N - FrameSize; i += HopSize)
{
_samples.FastCopyTo(reInput, FrameSize, i);
_complexFft.Direct(reInput, imInput, re, im);
}
}
public double[] Spectrum(double[] input, bool scale)
{
int length = input.Length;
var fft = new Fft(length);
var re = new float[length];
var im = new float[length];
for (int i = 0; i < length; i++)
{
re[i] = (float)input[i];
im[i] = 0f;
}
fft.Direct(re, im);
var spectrum = Helper.ComputeSpectrum(length, re, im);
fft.Inverse(re, im);
for (int i = 0; i < length; i++)
{
input[i] = re[i];
}
return(spectrum);
}
/// <summary>
/// Process one frame (block)
/// </summary>
public void ProcessFrame()
{
var M = _kernel.Length;
_zeroblock.FastCopyTo(_blockIm, _fftSize);
_zeroblock.FastCopyTo(_blockRe, M - 1, 0, HopSize);
_fft.Direct(_blockRe, _blockIm);
for (var j = 0; j < _fftSize; j++)
{
_convRe[j] = (_blockRe[j] * _kernelSpectrumRe[j] - _blockIm[j] * _kernelSpectrumIm[j]) / _fftSize;
_convIm[j] = (_blockRe[j] * _kernelSpectrumIm[j] + _blockIm[j] * _kernelSpectrumRe[j]) / _fftSize;
}
_fft.Inverse(_convRe, _convIm);
for (var j = 0; j < M - 1; j++)
{
_convRe[j] += _lastSaved[j];
}
_convRe.FastCopyTo(_lastSaved, M - 1, HopSize);
_outputBufferOffset = 0;
_bufferOffset = 0;
}
/// <summary>
/// Constructor
/// </summary>
/// <param name="kernel"></param>
/// <param name="fftSize"></param>
public OlaBlockConvolver(IEnumerable <float> kernel, int fftSize)
{
_fftSize = MathUtils.NextPowerOfTwo(fftSize);
if (kernel.Count() > _fftSize)
{
throw new ArgumentException("Kernel length must not exceed the size of FFT!");
}
_fft = new Fft(_fftSize);
_kernel = kernel.ToArray();
_kernelSpectrumRe = _kernel.PadZeros(_fftSize);
_kernelSpectrumIm = new float[_fftSize];
_convRe = new float[_fftSize];
_convIm = new float[_fftSize];
_blockRe = new float[_fftSize];
_blockIm = new float[_fftSize];
_lastSaved = new float[_kernel.Length - 1];
_zeroblock = new float[_fftSize];
_fft.Direct(_kernelSpectrumRe, _kernelSpectrumIm);
Reset();
}
public override DiscreteSignal ApplyTo(DiscreteSignal signal,
FilteringMethod method = FilteringMethod.Auto)
{
var input = signal.Samples;
var output = new float[input.Length];
var posSynthesis = 0;
for (var posAnalysis = 0; posAnalysis + _fftSize < input.Length; posAnalysis += _hopSize)
{
input.FastCopyTo(_re, _fftSize, posAnalysis);
_zeroblock.FastCopyTo(_im, _fftSize);
_re.ApplyWindow(_window);
_fft.Direct(_re, _im);
for (var j = 0; j < _fftSize / 2 + 1; j++)
{
var mag = Math.Sqrt(_re[j] * _re[j] + _im[j] * _im[j]);
var phase = Math.Atan2(_im[j], _re[j]);
_re[j] = (float)mag;
_im[j] = 0;
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
_re[j] = _im[j] = 0.0f;
}
_fft.Inverse(_re, _im);
for (var j = 0; j < _re.Length; j++)
{
output[posSynthesis + j] += _re[j] * _window[j];
}
for (var j = 0; j < _hopSize; j++)
{
output[posSynthesis + j] *= _gain;
output[j] = Wet * output[j] + Dry * input[j];
}
posSynthesis += _hopSize;
}
for (; posSynthesis < output.Length; posSynthesis++)
{
output[posSynthesis] *= _gain;
output[posSynthesis] = Wet * output[posSynthesis] + Dry * input[posSynthesis];
}
return(new DiscreteSignal(signal.SamplingRate, output));
}
public void FFT(bool forward)
{
if (forward)
{
fft.Direct(re, im);
}
else
{
fft.Inverse(re, im);
}
}
public void TestComplexFft()
{
float[] re = { 0, 1, 2, 3, 4, 5, 6, 7 };
float[] im = new float[8];
var fft = new Fft(8);
fft.Direct(re, im);
Assert.That(re, Is.EqualTo(new float[] { 28, -4, -4, -4, -4, -4, -4, -4 }).Within(1e-5));
Assert.That(im, Is.EqualTo(new float[] { 0, 9.65685f, 4, 1.65685f, 0, -1.65685f, -4, -9.65685f }).Within(1e-5));
}
/// <summary>
/// Phase Vocoder algorithm
/// </summary>
/// <param name="signal"></param>
/// <param name="method"></param>
/// <returns></returns>
public DiscreteSignal ApplyTo(DiscreteSignal signal,
FilteringMethod method = FilteringMethod.Auto)
{
var input = signal.Samples;
var output = new float[(int)(input.Length * _stretch) + _fftSize];
var posSynthesis = 0;
for (var posAnalysis = 0; posAnalysis + _fftSize < input.Length; posAnalysis += _hopAnalysis)
{
input.FastCopyTo(_re, _fftSize, posAnalysis);
_zeroblock.FastCopyTo(_im, _fftSize);
_re.ApplyWindow(_window);
_fft.Direct(_re, _im);
for (var j = 0; j < _fftSize / 2 + 1; j++)
{
var mag = Math.Sqrt(_re[j] * _re[j] + _im[j] * _im[j]);
var phase = 2 * Math.PI * _rand.NextDouble();
_re[j] = (float)(mag * Math.Cos(phase));
_im[j] = (float)(mag * Math.Sin(phase));
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
_re[j] = _im[j] = 0.0f;
}
_fft.Inverse(_re, _im);
for (var j = 0; j < _re.Length; j++)
{
output[posSynthesis + j] += _re[j] * _window[j];
}
for (var j = 0; j < _hopSynthesis; j++)
{
output[posSynthesis + j] *= _gain;
}
posSynthesis += _hopSynthesis;
}
for (; posSynthesis < output.Length; posSynthesis++)
{
output[posSynthesis] *= _gain;
}
return(new DiscreteSignal(signal.SamplingRate, output));
}
public void TestInverseFftNormalized()
{
float[] re = { 1, 5, 3, 7, 2, 3, 0, 7 };
float[] im = new float[re.Length];
var fft = new Fft(8);
fft.Direct(re, im);
fft.InverseNorm(re, im);
Assert.That(re, Is.EqualTo(new[] { 1, 5, 3, 7, 2, 3, 0, 7 }).Within(1e-5));
}
/// <summary>
/// Fast convolution via FFT of real-valued signals.
/// </summary>
/// <param name="signal1"></param>
/// <param name="signal2"></param>
/// <returns></returns>
public static DiscreteSignal Convolve(DiscreteSignal signal1, DiscreteSignal signal2)
{
// prepare blocks in memory:
var length = signal1.Length + signal2.Length - 1;
var fftSize = MathUtils.NextPowerOfTwo(length);
var fft = new Fft(fftSize);
var real1 = new float[fftSize];
var imag1 = new float[fftSize];
var real2 = new float[fftSize];
var imag2 = new float[fftSize];
signal1.Samples.FastCopyTo(real1, signal1.Length);
signal2.Samples.FastCopyTo(real2, signal2.Length);
// 1) do FFT of both signals
fft.Direct(real1, imag1);
fft.Direct(real2, imag2);
// 2) do complex multiplication of spectra and normalize
for (var i = 0; i < fftSize; i++)
{
var re = real1[i] * real2[i] - imag1[i] * imag2[i];
var im = real1[i] * imag2[i] + imag1[i] * real2[i];
real1[i] = re / fftSize;
imag1[i] = im / fftSize;
}
// 3) do inverse FFT of resulting spectrum
fft.Inverse(real1, imag1);
// 4) return resulting meaningful part of the signal (truncate size to N + M - 1)
return(new DiscreteSignal(signal1.SamplingRate, real1).First(length));
}
public void TestInverseFft()
{
float[] re = { 1, 5, 3, 7, 2, 3, 0, 7 };
float[] im = new float[re.Length];
var fft = new Fft(8);
fft.Direct(re, im);
fft.Inverse(re, im);
Assert.That(re, Is.EqualTo(new[] { 8, 40, 24, 56, 16, 24, 0, 56 }).Within(1e-5));
// re[i] * 8, i = 0..7
}
/// <summary>
/// Direct transform
/// </summary>
/// <param name="re"></param>
public void Direct(float[] re)
{
for (var i = 0; i < _im.Length; i++)
{
_im[i] = 0;
}
_fft.Direct(re, _im);
for (var i = 0; i < re.Length; i++)
{
re[i] -= _im[i];
}
}
/// <summary>
/// Process one frame (block)
/// </summary>
public void ProcessFrame()
{
_zeroblock.FastCopyTo(_im, _fftSize);
_dl.FastCopyTo(_re, _fftSize);
_re.ApplyWindow(_window);
_fft.Direct(_re, _im);
for (var j = 0; j <= _fftSize / 2; j++)
{
var mag = Math.Sqrt(_re[j] * _re[j] + _im[j] * _im[j]);
var phase = 2 * Math.PI * _rand.NextDouble();
_filteredRe[j] = (float)(mag * Math.Cos(phase));
_filteredIm[j] = (float)(mag * Math.Sin(phase));
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
_filteredRe[j] = _filteredIm[j] = 0.0f;
}
_fft.Inverse(_filteredRe, _filteredIm);
_filteredRe.ApplyWindow(_window);
for (var j = 0; j < _overlapSize; j++)
{
_filteredRe[j] += _lastSaved[j];
}
_filteredRe.FastCopyTo(_lastSaved, _overlapSize, _hopSize);
for (var i = 0; i < _filteredRe.Length; i++) // Wet / Dry mix
{
_filteredRe[i] *= Wet * 2 / _fftSize;
_filteredRe[i] += _dl[i] * Dry;
}
_dl.FastCopyTo(_dl, _overlapSize, _hopSize);
_inOffset = _overlapSize;
_outOffset = 0;
}
public static void ApplyFftToSignal(string filePath)
{
Console.WriteLine($"Applying FFT to {filePath} file");
using (var afr = new FileStream(filePath, FileMode.Open))
{
// create a signal file
var waveFile = new WaveFile(afr, false);
DiscreteSignal signal = waveFile[Channels.Left];
float[] real = signal.First(1024).Samples;
float[] imag = new float[1024];
var fft = new Fft(1024);
fft.Direct(real, imag); // in-place FFT
Console.WriteLine($"FFT size: {fft.Size}");
}
}
/// <summary>
/// Spectral subtraction algorithm according to
///
/// [1979] M. Berouti, R. Schwartz, J. Makhoul
/// "Enhancement of Speech Corrupted by Acoustic Noise".
///
/// </summary>
/// <param name="signal"></param>
/// <param name="noise"></param>
/// <param name="fftSize"></param>
/// <param name="hopSize"></param>
/// <returns></returns>
public static DiscreteSignal SpectralSubtract(DiscreteSignal signal,
DiscreteSignal noise,
int fftSize = 1024,
int hopSize = 410)
{
var input = signal.Samples;
var output = new float[input.Length];
const float beta = 0.009f;
const float alphaMin = 2f;
const float alphaMax = 5f;
const float snrMin = -5f;
const float snrMax = 20f;
const float k = (alphaMin - alphaMax) / (snrMax - snrMin);
const float b = alphaMax - k * snrMin;
var fft = new Fft(fftSize);
var hannWindow = Window.OfType(WindowTypes.Hann, fftSize);
var windowSquared = hannWindow.Select(w => w * w).ToArray();
var windowSum = new float[output.Length];
var re = new float[fftSize];
var im = new float[fftSize];
var zeroblock = new float[fftSize];
// estimate noise power spectrum
var noiseAcc = new float[fftSize / 2 + 1];
var noiseEstimate = new float[fftSize / 2 + 1];
var numFrames = 0;
var pos = 0;
for (; pos + fftSize < noise.Length; pos += hopSize, numFrames++)
{
noise.Samples.FastCopyTo(re, fftSize, pos);
zeroblock.FastCopyTo(im, fftSize);
fft.Direct(re, im);
for (var j = 0; j <= fftSize / 2; j++)
{
noiseAcc[j] += re[j] * re[j] + im[j] * im[j];
}
}
// (including smoothing)
for (var j = 1; j < fftSize / 2; j++)
{
noiseEstimate[j] = (noiseAcc[j - 1] + noiseAcc[j] + noiseAcc[j + 1]) / (3 * numFrames);
}
noiseEstimate[0] /= numFrames;
noiseEstimate[fftSize / 2] /= numFrames;
// spectral subtraction
for (pos = 0; pos + fftSize < input.Length; pos += hopSize)
{
input.FastCopyTo(re, fftSize, pos);
zeroblock.FastCopyTo(im, fftSize);
re.ApplyWindow(hannWindow);
fft.Direct(re, im);
for (var j = 0; j <= fftSize / 2; j++)
{
var power = re[j] * re[j] + im[j] * im[j];
var phase = Math.Atan2(im[j], re[j]);
var noisePower = noiseEstimate[j];
var snr = 10 * Math.Log10(power / noisePower);
var alpha = Math.Max(Math.Min(k * snr + b, alphaMax), alphaMin);
var diff = power - alpha * noisePower;
var mag = Math.Sqrt(Math.Max(diff, beta * noisePower));
re[j] = (float)(mag * Math.Cos(phase));
im[j] = (float)(mag * Math.Sin(phase));
}
for (var j = fftSize / 2 + 1; j < fftSize; j++)
{
re[j] = im[j] = 0.0f;
}
fft.Inverse(re, im);
for (var j = 0; j < re.Length; j++)
{
output[pos + j] += re[j] * hannWindow[j];
windowSum[pos + j] += windowSquared[j];
}
}
for (var j = 0; j < output.Length; j++)
{
if (windowSum[j] < 1e-3)
{
continue;
}
output[j] /= (windowSum[j] * fftSize / 2);
}
return(new DiscreteSignal(signal.SamplingRate, output));
}
/// <summary>
/// Phase locking procedure
/// </summary>
/// <param name="signal"></param>
/// <returns></returns>
public DiscreteSignal ApplyTo(DiscreteSignal signal,
FilteringMethod method = FilteringMethod.Auto)
{
var input = signal.Samples;
var output = new float[(int)(input.Length * _stretch) + _fftSize];
var peakCount = 0;
var posSynthesis = 0;
for (var posAnalysis = 0; posAnalysis + _fftSize < input.Length; posAnalysis += _hopAnalysis)
{
input.FastCopyTo(_re, _fftSize, posAnalysis);
_zeroblock.FastCopyTo(_im, _fftSize);
_re.ApplyWindow(_window);
_fft.Direct(_re, _im);
for (var j = 0; j < _mag.Length; j++)
{
_mag[j] = Math.Sqrt(_re[j] * _re[j] + _im[j] * _im[j]);
_phase[j] = Math.Atan2(_im[j], _re[j]);
}
// spectral peaks in magnitude spectrum
peakCount = 0;
for (var j = 2; j < _mag.Length - 3; j++)
{
if (_mag[j] <= _mag[j - 1] || _mag[j] <= _mag[j - 2] ||
_mag[j] <= _mag[j + 1] || _mag[j] <= _mag[j + 2])
{
continue; // if not a peak
}
_peaks[peakCount++] = j;
}
_peaks[peakCount++] = _mag.Length - 1;
// assign phases at peaks to all neighboring frequency bins
var leftPos = 0;
for (var j = 0; j < peakCount - 1; j++)
{
var peakPos = _peaks[j];
var peakPhase = _phase[peakPos];
_delta[peakPos] = peakPhase - _prevPhase[peakPos];
var deltaUnwrapped = _delta[peakPos] - _hopAnalysis * _omega[peakPos];
var deltaWrapped = MathUtils.Mod(deltaUnwrapped + Math.PI, 2 * Math.PI) - Math.PI;
var freq = _omega[peakPos] + deltaWrapped / _hopAnalysis;
_phaseTotal[peakPos] = _phaseTotal[peakPos] + _hopSynthesis * freq;
var rightPos = (_peaks[j] + _peaks[j + 1]) / 2;
for (var k = leftPos; k < rightPos; k++)
{
_phaseTotal[k] = _phaseTotal[peakPos] + _phase[k] - _phase[peakPos];
_prevPhase[k] = _phase[k];
_re[k] = (float)(_mag[k] * Math.Cos(_phaseTotal[k]));
_im[k] = (float)(_mag[k] * Math.Sin(_phaseTotal[k]));
}
leftPos = rightPos;
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
_re[j] = _im[j] = 0.0f;
}
_fft.Inverse(_re, _im);
for (var j = 0; j < _re.Length; j++)
{
output[posSynthesis + j] += _re[j] * _window[j];
}
for (var j = 0; j < _hopSynthesis; j++)
{
output[posSynthesis + j] *= _gain;
}
posSynthesis += _hopSynthesis;
}
for (; posSynthesis < output.Length; posSynthesis++)
{
output[posSynthesis] *= _gain;
}
return(new DiscreteSignal(signal.SamplingRate, output));
}
/// <summary>
/// Process one frame (block)
/// </summary>
public void ProcessFrame()
{
_zeroblock.FastCopyTo(_im, _fftSize);
_dl.FastCopyTo(_re, _fftSize);
_re.ApplyWindow(_window);
_fft.Direct(_re, _im);
var nextPhase = (float)(2 * Math.PI * _hopSize / _fftSize);
for (var j = 0; j < _fftSize / 2 + 1; j++)
{
_mag[j] = (float)Math.Sqrt(_re[j] * _re[j] + _im[j] * _im[j]);
_phase[j] = (float)Math.Atan2(_im[j], _re[j]);
var delta = _phase[j] - _prevPhase[j];
_prevPhase[j] = _phase[j];
delta -= j * nextPhase;
var deltaWrapped = MathUtils.Mod(delta + Math.PI, 2 * Math.PI) - Math.PI;
_phase[j] = _freqResolution * (j + (float)deltaWrapped / nextPhase);
}
_zeroblock.FastCopyTo(_re, _fftSize);
_zeroblock.FastCopyTo(_im, _fftSize);
// "stretch" spectrum:
var stretchPos = 0;
for (var j = 0; j <= _fftSize / 2 && stretchPos <= _fftSize / 2; j++)
{
_re[stretchPos] += _mag[j];
_im[stretchPos] = _phase[j] * _shift;
stretchPos = (int)(j * _shift);
}
for (var j = 0; j <= _fftSize / 2; j++)
{
var mag = _re[j];
var freqIndex = (_im[j] - j * _freqResolution) / _freqResolution;
_phaseTotal[j] += nextPhase * (freqIndex + j);
_filteredRe[j] = (float)(mag * Math.Cos(_phaseTotal[j]));
_filteredIm[j] = (float)(mag * Math.Sin(_phaseTotal[j]));
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
_filteredRe[j] = _filteredIm[j] = 0.0f;
}
_fft.Inverse(_filteredRe, _filteredIm);
_filteredRe.ApplyWindow(_window);
for (var j = 0; j < _overlapSize; j++)
{
_filteredRe[j] += _lastSaved[j];
}
_filteredRe.FastCopyTo(_lastSaved, _overlapSize, _hopSize);
for (var i = 0; i < _filteredRe.Length; i++) // Wet / Dry mix
{
_filteredRe[i] *= Wet * _gain;
_filteredRe[i] += _dl[i] * Dry;
}
_dl.FastCopyTo(_dl, _overlapSize, _hopSize);
_inOffset = _overlapSize;
_outOffset = 0;
}
/// <summary>
/// Phase Vocoder algorithm
/// </summary>
/// <param name="signal"></param>
/// <param name="filteringOptions"></param>
/// <returns></returns>
public DiscreteSignal ApplyTo(DiscreteSignal signal,
FilteringOptions filteringOptions = FilteringOptions.Auto)
{
var stretch = (float)_hopSynthesis / _hopAnalysis;
var input = signal.Samples;
var output = new float[(int)(input.Length * stretch) + _fftSize];
var fft = new Fft(_fftSize);
var hannWindow = Window.OfType(WindowTypes.Hann, _fftSize);
var ratio = _fftSize / (2.0f * _hopAnalysis);
var norm = 4.0f / (_fftSize * ratio);
var omega = Enumerable.Range(0, _fftSize / 2 + 1)
.Select(f => 2 * Math.PI * f / _fftSize)
.ToArray();
var re = new float[_fftSize];
var im = new float[_fftSize];
var zeroblock = new float[_fftSize];
var prevPhase = new double[_fftSize / 2 + 1];
var phaseTotal = new double[_fftSize / 2 + 1];
var posSynthesis = 0;
for (var posAnalysis = 0; posAnalysis + _fftSize < input.Length; posAnalysis += _hopAnalysis)
{
input.FastCopyTo(re, _fftSize, posAnalysis);
zeroblock.FastCopyTo(im, _fftSize);
re.ApplyWindow(hannWindow);
fft.Direct(re, im);
for (var j = 0; j < _fftSize / 2 + 1; j++)
{
var mag = Math.Sqrt(re[j] * re[j] + im[j] * im[j]);
var phase = Math.Atan2(im[j], re[j]);
var delta = phase - prevPhase[j];
var deltaUnwrapped = delta - _hopAnalysis * omega[j];
var deltaWrapped = MathUtils.Mod(deltaUnwrapped + Math.PI, 2 * Math.PI) - Math.PI;
var freq = omega[j] + deltaWrapped / _hopAnalysis;
phaseTotal[j] += _hopSynthesis * freq;
prevPhase[j] = phase;
re[j] = (float)(mag * Math.Cos(phaseTotal[j]));
im[j] = (float)(mag * Math.Sin(phaseTotal[j]));
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
re[j] = im[j] = 0.0f;
}
fft.Inverse(re, im);
for (var j = 0; j < re.Length; j++)
{
output[posSynthesis + j] += re[j] * hannWindow[j] * norm;
}
posSynthesis += _hopSynthesis;
}
return(new DiscreteSignal(signal.SamplingRate, output));
}
/// <summary>
/// Phase Vocoder algorithm
/// </summary>
/// <param name="signal"></param>
/// <param name="method"></param>
/// <returns></returns>
public DiscreteSignal ApplyTo(DiscreteSignal signal,
FilteringMethod method = FilteringMethod.Auto)
{
var input = signal.Samples;
var output = new float[(int)(input.Length * _stretch) + _fftSize];
var posSynthesis = 0;
for (var posAnalysis = 0; posAnalysis + _fftSize < input.Length; posAnalysis += _hopAnalysis)
{
input.FastCopyTo(_re, _fftSize, posAnalysis);
_zeroblock.FastCopyTo(_im, _fftSize);
_re.ApplyWindow(_window);
_fft.Direct(_re, _im);
for (var j = 0; j < _fftSize / 2 + 1; j++)
{
var mag = Math.Sqrt(_re[j] * _re[j] + _im[j] * _im[j]);
var phase = Math.Atan2(_im[j], _re[j]);
var delta = phase - _prevPhase[j];
var deltaUnwrapped = delta - _hopAnalysis * _omega[j];
var deltaWrapped = MathUtils.Mod(deltaUnwrapped + Math.PI, 2 * Math.PI) - Math.PI;
var freq = _omega[j] + deltaWrapped / _hopAnalysis;
_phaseTotal[j] += _hopSynthesis * freq;
_prevPhase[j] = phase;
_re[j] = (float)(mag * Math.Cos(_phaseTotal[j]));
_im[j] = (float)(mag * Math.Sin(_phaseTotal[j]));
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
_re[j] = _im[j] = 0.0f;
}
_fft.Inverse(_re, _im);
for (var j = 0; j < _re.Length; j++)
{
output[posSynthesis + j] += _re[j] * _window[j];
}
for (var j = 0; j < _hopSynthesis; j++)
{
output[posSynthesis + j] *= _gain;
}
posSynthesis += _hopSynthesis;
}
for (; posSynthesis < output.Length; posSynthesis++)
{
output[posSynthesis] *= _gain;
}
return(new DiscreteSignal(signal.SamplingRate, output));
}
/// <summary>
/// Phase Vocoder algorithm
/// </summary>
/// <param name="signal"></param>
/// <param name="filteringOptions"></param>
/// <returns></returns>
public DiscreteSignal ApplyTo(DiscreteSignal signal,
FilteringOptions filteringOptions = FilteringOptions.Auto)
{
if (_phaseLocking)
{
return(PhaseLocking(signal));
}
var input = signal.Samples;
var output = new float[(int)(input.Length * _stretch) + _fftSize];
var windowSum = new float[output.Length];
var re = new float[_fftSize];
var im = new float[_fftSize];
var zeroblock = new float[_fftSize];
var prevPhase = new double[_fftSize / 2 + 1];
var phaseTotal = new double[_fftSize / 2 + 1];
var posSynthesis = 0;
for (var posAnalysis = 0; posAnalysis + _fftSize < input.Length; posAnalysis += _hopAnalysis)
{
input.FastCopyTo(re, _fftSize, posAnalysis);
zeroblock.FastCopyTo(im, _fftSize);
re.ApplyWindow(_window);
_fft.Direct(re, im);
for (var j = 0; j < _fftSize / 2 + 1; j++)
{
var mag = Math.Sqrt(re[j] * re[j] + im[j] * im[j]);
var phase = Math.Atan2(im[j], re[j]);
var delta = phase - prevPhase[j];
var deltaUnwrapped = delta - _hopAnalysis * _omega[j];
var deltaWrapped = MathUtils.Mod(deltaUnwrapped + Math.PI, 2 * Math.PI) - Math.PI;
var freq = _omega[j] + deltaWrapped / _hopAnalysis;
phaseTotal[j] += _hopSynthesis * freq;
prevPhase[j] = phase;
re[j] = (float)(mag * Math.Cos(phaseTotal[j]));
im[j] = (float)(mag * Math.Sin(phaseTotal[j]));
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
re[j] = im[j] = 0.0f;
}
_fft.Inverse(re, im);
for (var j = 0; j < re.Length; j++)
{
output[posSynthesis + j] += re[j] * _window[j];
windowSum[posSynthesis + j] += _windowSquared[j];
}
posSynthesis += _hopSynthesis;
}
for (var j = 0; j < output.Length; j++)
{
if (windowSum[j] < 1e-3)
{
continue;
}
output[j] /= (windowSum[j] * _fftSize / 2);
}
return(new DiscreteSignal(signal.SamplingRate, output));
}
public DiscreteSignal ApplyTo(DiscreteSignal signal1,
DiscreteSignal signal2,
FilteringMethod method = FilteringMethod.Auto)
{
Guard.AgainstInequality(signal1.SamplingRate, signal2.SamplingRate, "1st signal sampling rate", "2nd signal sampling rate");
var input1 = signal1.Samples;
var input2 = signal2.Samples;
var output = new float[input1.Length];
var windowSum = new float[output.Length];
var posMorph = 0;
var endMorph = signal2.Length - _fftSize;
var posSynthesis = 0;
for (var posAnalysis = 0; posAnalysis + _fftSize < input1.Length; posAnalysis += _hopSize, posMorph += _hopSize)
{
input1.FastCopyTo(_re1, _fftSize, posAnalysis);
_zeroblock.FastCopyTo(_im1, _fftSize);
if (posMorph > endMorph)
{
posMorph = 0;
}
input2.FastCopyTo(_re2, _fftSize, posMorph);
_zeroblock.FastCopyTo(_im2, _fftSize);
_re1.ApplyWindow(_window);
_re2.ApplyWindow(_window);
_fft.Direct(_re1, _im1);
_fft.Direct(_re2, _im2);
for (var j = 0; j < _fftSize / 2 + 1; j++)
{
var mag1 = Math.Sqrt(_re1[j] * _re1[j] + _im1[j] * _im1[j]);
var phase1 = Math.Atan2(_im1[j], _re1[j]);
var mag2 = Math.Sqrt(_re2[j] * _re2[j] + _im2[j] * _im2[j]);
var phase2 = Math.Atan2(_im2[j], _re2[j]);
_re1[j] = (float)(mag1 * Math.Cos(phase2));
_im1[j] = (float)(mag1 * Math.Sin(phase2));
}
for (var j = _fftSize / 2 + 1; j < _fftSize; j++)
{
_re1[j] = _im1[j] = 0.0f;
}
_fft.Inverse(_re1, _im1);
for (var j = 0; j < _re1.Length; j++)
{
output[posSynthesis + j] += _re1[j] * _window[j];
}
posSynthesis += _hopSize;
}
posMorph = 0;
for (var j = 0; j < output.Length; j++, posMorph++)
{
output[j] /= _fftSize;
if (posMorph > endMorph)
{
posMorph = 0;
}
output[j] = Wet * output[j] + Dry * signal2[posMorph];
}
return(new DiscreteSignal(signal1.SamplingRate, output));
}
/// <summary>
/// Method implements block convolution of signals (using either OLA or OLS algorithm)
/// </summary>
/// <param name="signal"></param>
/// <param name="kernel"></param>
/// <param name="fftSize"></param>
/// <param name="method"></param>
/// <returns></returns>
public static DiscreteSignal BlockConvolve(DiscreteSignal signal,
DiscreteSignal kernel,
int fftSize,
BlockConvolution method = BlockConvolution.OverlapAdd)
{
var m = kernel.Length;
if (m > fftSize)
{
throw new ArgumentException("Kernel length must not exceed the size of FFT!");
}
var fft = new Fft(fftSize);
// pre-compute kernel's FFT:
var kernelReal = kernel.Samples.PadZeros(fftSize);
var kernelImag = new float[fftSize];
fft.Direct(kernelReal, kernelImag);
// reserve space for current signal block:
var blockReal = new float[fftSize];
var blockImag = new float[fftSize];
var zeroblock = new float[fftSize];
// reserve space for resulting spectrum at each step:
var spectrumReal = new float[fftSize];
var spectrumImag = new float[fftSize];
var filtered = new DiscreteSignal(signal.SamplingRate, signal.Length);
var hopSize = fftSize - m + 1;
if (method == BlockConvolution.OverlapAdd)
{
var i = 0;
while (i < signal.Length)
{
// ============================== FFT CONVOLUTION SECTION =================================
// for better performance we inline FFT convolution here;
// alternatively, we could simply write:
//
// var res = Convolve(signal[i, i + hopSize], kernel);
//
// ...but that would require unnecessary memory allocations
// and recalculating of kernel FFT at each step.
zeroblock.FastCopyTo(blockReal, fftSize);
zeroblock.FastCopyTo(blockImag, fftSize);
signal.Samples.FastCopyTo(blockReal, Math.Min(hopSize, signal.Length - i), i);
// 1) do FFT of a signal block:
fft.Direct(blockReal, blockImag);
// 2) do complex multiplication of spectra
for (var j = 0; j < fftSize; j++)
{
spectrumReal[j] = (blockReal[j] * kernelReal[j] - blockImag[j] * kernelImag[j]) / fftSize;
spectrumImag[j] = (blockReal[j] * kernelImag[j] + blockImag[j] * kernelReal[j]) / fftSize;
}
// 3) do inverse FFT of resulting spectrum
fft.Inverse(spectrumReal, spectrumImag);
// ========================================================================================
for (var j = 0; j < m - 1 && i + j < filtered.Length; j++)
{
filtered[i + j] += spectrumReal[j];
}
for (var j = m - 1; j < spectrumReal.Length && i + j < filtered.Length; j++)
{
filtered[i + j] = spectrumReal[j];
}
i += hopSize;
}
return(filtered);
}
else
{
signal = new DiscreteSignal(signal.SamplingRate, m - 1).Concatenate(signal);
var i = 0;
while (i < signal.Length)
{
// ============================== FFT CONVOLUTION SECTION =================================
signal.Samples.FastCopyTo(blockReal, Math.Min(fftSize, signal.Length - i), i);
zeroblock.FastCopyTo(blockImag, fftSize);
// 1) do FFT of a signal block:
fft.Direct(blockReal, blockImag);
// 2) do complex multiplication of spectra
for (var j = 0; j < fftSize; j++)
{
spectrumReal[j] = (blockReal[j] * kernelReal[j] - blockImag[j] * kernelImag[j]) / fftSize;
spectrumImag[j] = (blockReal[j] * kernelImag[j] + blockImag[j] * kernelReal[j]) / fftSize;
}
// 3) do inverse FFT of resulting spectrum
fft.Inverse(spectrumReal, spectrumImag);
// ========================================================================================
for (var j = 0; j + m - 1 < spectrumReal.Length && i + j < filtered.Length; j++)
{
filtered[i + j] = spectrumReal[j + m - 1];
}
i += hopSize;
}
return(filtered);
}
}