/// <summary>
/// Perform an inverse mel scale and log.
/// </summary>
/// <param name="wavelet">mel scaled matrix</param>
/// <returns>matrix mel removed and un-logged (e.g. stftdata)</returns>
public Matrix InverseMelScaleAndLog(ref Matrix mel)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 5. Take Inverse Logarithm
// Divide with first triangle height in order to scale properly
for (int i = 0; i < mel.Rows; i++)
{
for (int j = 0; j < mel.Columns; j++)
{
mel.MatrixData[i][j] = Math.Pow(10, (mel.MatrixData[i][j] / 20)) / melScaleTriangleHeights[0];
}
}
// 4. Inverse Mel Scale using interpolation
// i.e. from e.g.
// mel=Rows: 40, Columns: 165 (average freq, time slice)
// to
// m=Rows: 1024, Columns: 165 (freq, time slice)
//Matrix m = filterWeights.Transpose() * mel;
Matrix m = new Matrix(filterWeights.Columns, mel.Columns);
InverseMelScaling(mel, m);
Mirage.Dbg.WriteLine("Inverse Mel Scale And Log - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(m);
}
/// <summary>
/// Mel Scale Haar Wavelet Transform and Compress
/// </summary>
/// <param name="m">matrix (stftdata)</param>
/// <returns>matrix mel scaled and wavelet'ed</returns>
public Matrix ApplyMelScaleAndWaveletCompress(ref Matrix m, out int lastHeight, out int lastWidth)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 4. Mel Scale Filterbank
// Mel-frequency is proportional to the logarithm of the linear frequency,
// reflecting similar effects in the human's subjective aural perception)
Matrix mel = filterWeights * m;
// 5. Take Logarithm
for (int i = 0; i < mel.Rows; i++)
{
for (int j = 0; j < mel.Columns; j++)
{
mel.MatrixData[i][j] = (mel.MatrixData[i][j] < 1.0 ? 0 : (20.0 * Math.Log10(mel.MatrixData[i][j])));
}
}
// 6. Perform the Wavelet Transform and Compress
Matrix waveletCompressed = ApplyWaveletCompression(ref mel, out lastHeight, out lastWidth);
Mirage.Dbg.WriteLine("Mel Scale And Wavelet Compression - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(waveletCompressed);
}
/// <summary>
/// Perform an inverse mfcc. E.g. perform an idct and inverse Mel Filterbands and return stftdata
/// </summary>
/// <param name="mfcc">mfcc matrix</param>
/// <returns>matrix idct'ed and mel removed (e.g. stftdata)</returns>
public Matrix InverseMelScaleDCT(ref Matrix mfcc)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 6. Perform the IDCT (Inverse Discrete Cosine Transform)
Matrix mel = dct.Transpose() * mfcc;
// 5. Take Inverse Logarithm
for (int i = 0; i < mel.Rows; i++)
{
for (int j = 0; j < mel.Columns; j++)
{
mel.MatrixData[i][j] = Math.Pow(10, (mel.MatrixData[i][j] / 20)) / melScaleTriangleHeights[0];
}
}
// 4. Inverse Mel Scale using interpolation
// i.e. from e.g.
// mel=Rows: 40, Columns: 165 (average freq, time slice)
// to
// m=Rows: 1024, Columns: 165 (freq, time slice)
//Matrix m = filterWeights.Transpose() * mel;
Matrix m = new Matrix(filterWeights.Columns, mel.Columns);
InverseMelScaling(mel, m);
Mirage.Dbg.WriteLine("imfcc (MfccMirage-MirageWay) Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(m);
}
/// <summary>
/// Perform an inverse haar wavelet mel scaled transform. E.g. perform an ihaar2d and inverse Mel Filterbands and return stftdata
/// </summary>
/// <param name="wavelet">wavelet matrix</param>
/// <returns>matrix inverse wavelet'ed and mel removed (e.g. stftdata)</returns>
public Matrix InverseMelScaleAndWaveletCompress(ref Matrix wavelet, int firstHeight, int firstWidth)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 6. Ucompress and then perform the Inverse Wavelet Transform
Matrix mel = InverseWaveletCompression(ref wavelet, firstHeight, firstWidth, melScaleFreqsIndex.Length - 2, wavelet.Columns);
// 5. Take Inverse Logarithm
// Divide with first triangle height in order to scale properly
for (int i = 0; i < mel.Rows; i++)
{
for (int j = 0; j < mel.Columns; j++)
{
mel.MatrixData[i][j] = Math.Pow(10, (mel.MatrixData[i][j] / 20)) / melScaleTriangleHeights[0];
}
}
// 4. Inverse Mel Scale using interpolation
// i.e. from e.g.
// mel=Rows: 40, Columns: 165 (average freq, time slice)
// to
// m=Rows: 1024, Columns: 165 (freq, time slice)
//Matrix m = filterWeights.Transpose() * mel;
Matrix m = new Matrix(filterWeights.Columns, mel.Columns);
InverseMelScaling(mel, m);
Mirage.Dbg.WriteLine("Inverse Mel Scale and Wavelet Compression - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(m);
}
/// <summary>
/// Apply internal DCT and Mel Filterbands
/// This method is faster than ApplyComirvaWay since it uses fewer loops.
/// </summary>
/// <param name="m">matrix (stftdata)</param>
/// <returns>matrix mel scaled and dct'ed</returns>
public Matrix ApplyMelScaleDCT(ref Matrix m)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 4. Mel Scale Filterbank
// Mel-frequency is proportional to the logarithm of the linear frequency,
// reflecting similar effects in the human's subjective aural perception)
Matrix mel = filterWeights * m;
// 5. Take Logarithm
for (int i = 0; i < mel.Rows; i++)
{
for (int j = 0; j < mel.Columns; j++)
{
mel.MatrixData[i][j] = (mel.MatrixData[i][j] < 1.0 ? 0 : (20.0 * Math.Log10(mel.MatrixData[i][j])));
}
}
// 6. DCT (Discrete Cosine Transform)
Matrix mfcc = dct * mel;
Mirage.Dbg.WriteLine("mfcc (MfccMirage-MirageWay) Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(mfcc);
}
/// <summary>
/// Perform an inverse DCT
/// </summary>
/// <param name="mfcc">dct matrix</param>
/// <returns>matrix idct'ed (e.g. logSpectrogram)</returns>
public Matrix InverseDCT(ref Matrix input)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 6. Perform the IDCT (Inverse Discrete Cosine Transform)
Matrix m = dct.Transpose() * input;
Mirage.Dbg.WriteLine("InverseDCT Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(m);
}
/// <summary>
/// DCT
/// </summary>
/// <param name="m">matrix (logSpectrogram)</param>
/// <returns>matrix dct'ed</returns>
public Matrix ApplyDCT(ref Matrix m)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 6. DCT (Discrete Cosine Transform)
m = dct * m;
Mirage.Dbg.WriteLine("ApplyDCT Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(m);
}
/// <summary>
/// Perform an inverse decompressed haar wavelet transform. E.g. perform an ihaar2d and return logSpectrogram
/// </summary>
/// <param name="wavelet">wavelet matrix</param>
/// <returns>matrix inverse wavelet'ed (e.g. logSpectrogram)</returns>
public Matrix InverseWaveletCompression(ref Matrix wavelet, int firstHeight, int firstWidth, int rows, int columns)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// Resize, e.g. Uncompress
wavelet = wavelet.Resize(rows, columns);
// 6. Perform the Inverse Wavelet Transform
Matrix m = wavelet.Copy();
Wavelets.Compress.WaveletDecompress.Decompress2D(m.MatrixData, numberWaveletTransforms, firstHeight, firstWidth);
Mirage.Dbg.WriteLine("Inverse Wavelet Compression - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(m);
}
/// <summary>
/// Haar Wavelet Transform and Compress
/// </summary>
/// <param name="m">matrix (logSpectrogram)</param>
/// <returns>matrix wavelet'ed</returns>
public Matrix ApplyWaveletCompression(ref Matrix m, out int lastHeight, out int lastWidth)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// Wavelet Transform
Matrix wavelet = m.Copy();
Wavelets.Compress.WaveletCompress.HaarTransform2D(wavelet.MatrixData, numberWaveletTransforms, out lastHeight, out lastWidth);
// Compress
Matrix waveletCompressed = wavelet.Resize(numberCoefficients, wavelet.Columns);
Mirage.Dbg.WriteLine("Wavelet Compression - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(waveletCompressed);
}
/// <summary>
/// Perform an inverse STFT and return the audiodata
/// </summary>
/// <param name="stft">A matrix with the STFT</param>
/// <returns>Audio data</returns>
/// <see cref="http://stackoverflow.com/questions/1230906/reverse-spectrogram-a-la-aphex-twin-in-matlab">Reverse Spectrogram A La Aphex Twin in MATLAB</see>
public double[] InverseStft(Matrix stft) {
var t = new Mirage.DbgTimer();
t.Start();
// stft is a Matrix with "winsize" Rows and "hops" Columns
int columns = stft.Columns;
int signalLengh = winsize + (columns)*hopsize; // PIN: Removed -1 from (columns-1)
var signal = new double[signalLengh];
// Take the ifft of each column of pixels and piece together the results.
for (int i = 0; i < columns; i++) {
fft.ComputeInverseComirvaMatrixUsingLomontTableFFT(stft, i, ref signal, winsize, hopsize);
//fft.ComputeInverseComirvaMatrixUsingLomontRealFFT(stft, i, ref signal, winsize, hopsize);
}
Mirage.Dbg.WriteLine("Perform Inverse Short Term Fourier Transform (ComputeComirvaMatrix) - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return signal;
}
/// <summary>
/// Apply the STFT on the audiodata
/// </summary>
/// <param name="audiodata">Audiodata to apply the STFT on</param>
/// <returns>A matrix with the result of the STFT</returns>
public Matrix Apply(float[] audiodata)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
int hops = (audiodata.Length - winsize)/ hopsize; // PIN: Removed + 1
// Create a Matrix with "winsize" Rows and "hops" Columns
// Matrix[Row, Column]
Matrix stft = new Matrix(winsize/2, hops);
for (int i = 0; i < hops; i++) {
// Lomont RealFFT seems to be the fastest option
//fft.ComputeComirvaMatrixUsingFftw(ref stft, i, audiodata, i*hopsize);
//fft.ComputeComirvaMatrixUsingLomontTableFFT(ref stft, i, audiodata, i*hopsize);
fft.ComputeComirvaMatrixUsingLomontRealFFT(ref stft, i, audiodata, i*hopsize);
}
Mirage.Dbg.WriteLine("Perform Short Term Fourier Transform (ComputeComirvaMatrix) - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return stft;
}
/// <summary>
/// Mel Scale Haar Wavelet Transform
/// </summary>
/// <param name="m">matrix (stftdata)</param>
/// <returns>matrix mel scaled and wavelet'ed</returns>
public Matrix ApplyMelScaleWaveletPadding(ref Matrix m)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 4. Mel Scale Filterbank
// Mel-frequency is proportional to the logarithm of the linear frequency,
// reflecting similar effects in the human's subjective aural perception)
Matrix mel = filterWeights * m;
// 5. Take Logarithm
for (int i = 0; i < mel.Rows; i++)
{
for (int j = 0; j < mel.Columns; j++)
{
mel.MatrixData[i][j] = (mel.MatrixData[i][j] < 1.0 ? 0 : (20.0 * Math.Log10(mel.MatrixData[i][j])));
}
}
// 6. Wavelet Transform
// make sure the matrix is square before transforming (by zero padding)
Matrix resizedMatrix;
if (!mel.IsSymmetric() || !MathUtils.IsPowerOfTwo(mel.Rows))
{
int size = (mel.Rows > mel.Columns ? mel.Rows : mel.Columns);
int sizePow2 = MathUtils.NextPowerOfTwo(size);
resizedMatrix = mel.Resize(sizePow2, sizePow2);
}
else
{
resizedMatrix = mel;
}
Matrix wavelet = WaveletUtils.HaarWaveletTransform(resizedMatrix.MatrixData, true);
Mirage.Dbg.WriteLine("Wavelet Mel Scale And Wavelet Compression Padding - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(wavelet);
}
/// <summary>
/// Perform an inverse STFT and return the audiodata
/// </summary>
/// <param name="stft">A matrix with the STFT</param>
/// <returns>Audio data</returns>
/// <see cref="http://stackoverflow.com/questions/1230906/reverse-spectrogram-a-la-aphex-twin-in-matlab">Reverse Spectrogram A La Aphex Twin in MATLAB</see>
public double[] InverseStft(Matrix stft)
{
var t = new Mirage.DbgTimer();
t.Start();
// stft is a Matrix with "winsize" Rows and "hops" Columns
int columns = stft.Columns;
int signalLengh = winsize + (columns) * hopsize; // PIN: Removed -1 from (columns-1)
var signal = new double[signalLengh];
// Take the ifft of each column of pixels and piece together the results.
for (int i = 0; i < columns; i++)
{
fft.ComputeInverseComirvaMatrixUsingLomontTableFFT(stft, i, ref signal, winsize, hopsize);
//fft.ComputeInverseComirvaMatrixUsingLomontRealFFT(stft, i, ref signal, winsize, hopsize);
}
Mirage.Dbg.WriteLine("Perform Inverse Short Term Fourier Transform (ComputeComirvaMatrix) - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(signal);
}
/// <summary>
/// Apply the STFT on the audiodata
/// </summary>
/// <param name="audiodata">Audiodata to apply the STFT on</param>
/// <returns>A matrix with the result of the STFT</returns>
public Matrix Apply(float[] audiodata)
{
var t = new Mirage.DbgTimer();
t.Start();
int hops = (audiodata.Length - winsize) / hopsize; // PIN: Removed + 1
// Create a Matrix with "winsize" Rows and "hops" Columns
// Matrix[Row, Column]
var stft = new Matrix(winsize / 2, hops);
for (int i = 0; i < hops; i++)
{
// Lomont RealFFT seems to be the fastest option
//fft.ComputeComirvaMatrixUsingFftw(ref stft, i, audiodata, i*hopsize);
//fft.ComputeComirvaMatrixUsingLomontTableFFT(ref stft, i, audiodata, i*hopsize);
fft.ComputeComirvaMatrixUsingLomontRealFFT(ref stft, i, audiodata, i * hopsize);
}
Mirage.Dbg.WriteLine("Perform Short Term Fourier Transform (ComputeComirvaMatrix) - Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(stft);
}
/// <summary>
/// Apply internal DCT and Mel Filterbands utilising the Comirva Matrix methods
/// </summary>
/// <param name="m">matrix (stftdata)</param>
/// <returns>matrix mel scaled and dct'ed</returns>
public Matrix ApplyMelScaleDCTComirva(ref Matrix m)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 4. Mel Scale Filterbank
// Mel-frequency is proportional to the logarithm of the linear frequency,
// reflecting similar effects in the human's subjective aural perception)
m = filterWeights * m;
// 5. Take Logarithm
// to db
double log10 = 20 * (1 / Math.Log(10)); // log for base 10 and scale by factor 10
m.ThrunkAtLowerBoundary(1);
m.LogEquals();
m *= log10;
// 6. DCT (Discrete Cosine Transform)
m = dct * m;
Mirage.Dbg.WriteLine("mfcc (MfccMirage-ComirvaWay) Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return(m);
}
/// <summary>
/// Apply internal DCT and Mel Filterbands
/// This method is faster than ApplyComirvaWay since it uses fewer loops.
/// </summary>
/// <param name="m">matrix (stftdata)</param>
/// <returns>matrix mel scaled and dct'ed</returns>
public Matrix ApplyMelScaleDCT(ref Matrix m)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 4. Mel Scale Filterbank
// Mel-frequency is proportional to the logarithm of the linear frequency,
// reflecting similar effects in the human's subjective aural perception)
Matrix mel = filterWeights * m;
// 5. Take Logarithm
for (int i = 0; i < mel.Rows; i++) {
for (int j = 0; j < mel.Columns; j++) {
mel.MatrixData[i][j] = (mel.MatrixData[i][j] < 1.0 ? 0 : (20.0 * Math.Log10(mel.MatrixData[i][j])));
}
}
// 6. DCT (Discrete Cosine Transform)
Matrix mfcc = dct * mel;
Mirage.Dbg.WriteLine("mfcc (MfccMirage-MirageWay) Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return mfcc;
}
/// <summary>
/// Perform an inverse decompressed haar wavelet transform. E.g. perform an ihaar2d and return logSpectrogram
/// </summary>
/// <param name="wavelet">wavelet matrix</param>
/// <returns>matrix inverse wavelet'ed (e.g. logSpectrogram)</returns>
public Matrix InverseWaveletCompression(ref Matrix wavelet, int firstHeight, int firstWidth, int rows, int columns)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// Resize, e.g. Uncompress
wavelet = wavelet.Resize(rows, columns);
// 6. Perform the Inverse Wavelet Transform
Matrix m = wavelet.Copy();
Wavelets.Compress.WaveletDecompress.Decompress2D(m.MatrixData, numberWaveletTransforms, firstHeight, firstWidth);
Mirage.Dbg.WriteLine("Inverse Wavelet Compression Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return m;
}
/// <summary>
/// Perform an inverse haar wavelet mel scaled transform. E.g. perform an ihaar2d and inverse Mel Filterbands and return stftdata
/// </summary>
/// <param name="wavelet">wavelet matrix</param>
/// <returns>matrix inverse wavelet'ed and mel removed (e.g. stftdata)</returns>
public Matrix InverseMelScaleWaveletPadding(ref Matrix wavelet)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 6. Perform the Inverse Wavelet Transform
Matrix mel = WaveletUtils.InverseHaarWaveletTransform(wavelet.MatrixData);
// Resize (remove padding)
mel = mel.Resize(melScaleFreqsIndex.Length - 2, wavelet.Columns);
// 5. Take Inverse Logarithm
// Divide with first triangle height in order to scale properly
for (int i = 0; i < mel.Rows; i++) {
for (int j = 0; j < mel.Columns; j++) {
mel.MatrixData[i][j] = Math.Pow(10, (mel.MatrixData[i][j] / 20)) / melScaleTriangleHeights[0];
}
}
// 4. Inverse Mel Scale using interpolation
// i.e. from e.g.
// mel=Rows: 40, Columns: 165 (average freq, time slice)
// to
// m=Rows: 1024, Columns: 165 (freq, time slice)
//Matrix m = filterWeights.Transpose() * mel;
Matrix m = new Matrix(filterWeights.Columns, mel.Columns);
InverseMelScaling(mel, m);
Mirage.Dbg.WriteLine("Inverse Wavelet Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return m;
}
/// <summary>
/// Perform an inverse mfcc. E.g. perform an idct and inverse Mel Filterbands and return stftdata
/// </summary>
/// <param name="mfcc">mfcc matrix</param>
/// <returns>matrix idct'ed and mel removed (e.g. stftdata)</returns>
public Matrix InverseMelScaleDCT(ref Matrix mfcc)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 6. Perform the IDCT (Inverse Discrete Cosine Transform)
Matrix mel = dct.Transpose() * mfcc;
// 5. Take Inverse Logarithm
for (int i = 0; i < mel.Rows; i++) {
for (int j = 0; j < mel.Columns; j++) {
mel.MatrixData[i][j] = Math.Pow(10, (mel.MatrixData[i][j] / 20)) / melScaleTriangleHeights[0];
}
}
// 4. Inverse Mel Scale using interpolation
// i.e. from e.g.
// mel=Rows: 40, Columns: 165 (average freq, time slice)
// to
// m=Rows: 1024, Columns: 165 (freq, time slice)
//Matrix m = filterWeights.Transpose() * mel;
Matrix m = new Matrix(filterWeights.Columns, mel.Columns);
InverseMelScaling(mel, m);
Mirage.Dbg.WriteLine("imfcc (MfccMirage-MirageWay) Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return m;
}
/// <summary>
/// Perform an inverse mel scale and log.
/// </summary>
/// <param name="wavelet">mel scaled matrix</param>
/// <returns>matrix mel removed and un-logged (e.g. stftdata)</returns>
public Matrix InverseMelScaleAndLog(ref Matrix mel)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 5. Take Inverse Logarithm
// Divide with first triangle height in order to scale properly
for (int i = 0; i < mel.Rows; i++) {
for (int j = 0; j < mel.Columns; j++) {
mel.MatrixData[i][j] = Math.Pow(10, (mel.MatrixData[i][j] / 20)) / melScaleTriangleHeights[0];
}
}
// 4. Inverse Mel Scale using interpolation
// i.e. from e.g.
// mel=Rows: 40, Columns: 165 (average freq, time slice)
// to
// m=Rows: 1024, Columns: 165 (freq, time slice)
//Matrix m = filterWeights.Transpose() * mel;
Matrix m = new Matrix(filterWeights.Columns, mel.Columns);
InverseMelScaling(mel, m);
Mirage.Dbg.WriteLine("InverseMelScaleAndLog Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return m;
}
/// <summary>
/// Perform an inverse DCT
/// </summary>
/// <param name="mfcc">dct matrix</param>
/// <returns>matrix idct'ed (e.g. logSpectrogram)</returns>
public Matrix InverseDCT(ref Matrix input)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 6. Perform the IDCT (Inverse Discrete Cosine Transform)
Matrix m = dct.Transpose() * input;
Mirage.Dbg.WriteLine("InverseDCT Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return m;
}
/// <summary>
/// Haar Wavelet Transform and Compress
/// </summary>
/// <param name="m">matrix (logSpectrogram)</param>
/// <returns>matrix wavelet'ed</returns>
public Matrix ApplyWaveletCompression(ref Matrix m, out int lastHeight, out int lastWidth)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// Wavelet Transform
Matrix wavelet = m.Copy();
Wavelets.Compress.WaveletCompress.HaarTransform2D(wavelet.MatrixData, numberWaveletTransforms, out lastHeight, out lastWidth);
// Compress
Matrix waveletCompressed = wavelet.Resize(numberCoefficients, wavelet.Columns);
Mirage.Dbg.WriteLine("Wavelet Compression Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return waveletCompressed;
}
/// <summary>
/// Mel Scale Haar Wavelet Transform
/// </summary>
/// <param name="m">matrix (stftdata)</param>
/// <returns>matrix mel scaled and wavelet'ed</returns>
public Matrix ApplyMelScaleWaveletPadding(ref Matrix m)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 4. Mel Scale Filterbank
// Mel-frequency is proportional to the logarithm of the linear frequency,
// reflecting similar effects in the human's subjective aural perception)
Matrix mel = filterWeights * m;
// 5. Take Logarithm
for (int i = 0; i < mel.Rows; i++) {
for (int j = 0; j < mel.Columns; j++) {
mel.MatrixData[i][j] = (mel.MatrixData[i][j] < 1.0 ? 0 : (20.0 * Math.Log10(mel.MatrixData[i][j])));
}
}
// 6. Wavelet Transform
// make sure the matrix is square before transforming (by zero padding)
Matrix resizedMatrix;
if (!mel.IsSymmetric() || !MathUtils.IsPowerOfTwo(mel.Rows)) {
int size = (mel.Rows > mel.Columns ? mel.Rows : mel.Columns);
int sizePow2 = MathUtils.NextPowerOfTwo(size);
resizedMatrix = mel.Resize(sizePow2, sizePow2);
} else {
resizedMatrix = mel;
}
Matrix wavelet = WaveletUtils.HaarWaveletTransform(resizedMatrix.MatrixData, true);
Mirage.Dbg.WriteLine("Wavelet Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return wavelet;
}
/// <summary>
/// Mel Scale Haar Wavelet Transform and Compress
/// </summary>
/// <param name="m">matrix (stftdata)</param>
/// <returns>matrix mel scaled and wavelet'ed</returns>
public Matrix ApplyMelScaleWaveletCompression(ref Matrix m, out int lastHeight, out int lastWidth)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 4. Mel Scale Filterbank
// Mel-frequency is proportional to the logarithm of the linear frequency,
// reflecting similar effects in the human's subjective aural perception)
Matrix mel = filterWeights * m;
// 5. Take Logarithm
for (int i = 0; i < mel.Rows; i++) {
for (int j = 0; j < mel.Columns; j++) {
mel.MatrixData[i][j] = (mel.MatrixData[i][j] < 1.0 ? 0 : (20.0 * Math.Log10(mel.MatrixData[i][j])));
}
}
// 6. Perform the Wavelet Transform and Compress
Matrix waveletCompressed = ApplyWaveletCompression(ref mel, out lastHeight, out lastWidth);
Mirage.Dbg.WriteLine("Wavelet Compression Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return waveletCompressed;
}
/// <summary>
/// DCT
/// </summary>
/// <param name="m">matrix (logSpectrogram)</param>
/// <returns>matrix dct'ed</returns>
public Matrix ApplyDCT(ref Matrix m)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 6. DCT (Discrete Cosine Transform)
m = dct * m;
Mirage.Dbg.WriteLine("ApplyDCT Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return m;
}
private static List<bool[]> GetFingerprintSignatures(FingerprintService fingerprintService, float[] samples, string name)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// work config
WorkUnitParameterObject param = new WorkUnitParameterObject();
param.FingerprintingConfiguration = fingerprintingConfigCreation;
// Get fingerprints
double[][] LogSpectrogram;
List<double[][]> spectralImages;
List<bool[]> fingerprints = fingerprintService.CreateFingerprintsFromAudioSamples(samples, param, out LogSpectrogram, out spectralImages);
#if DEBUG
if (Analyzer.DEBUG_INFO_VERBOSE) {
// Image Service
ImageService imageService =
new ImageService(fingerprintService.SpectrumService, fingerprintService.WaveletService);
int width = param.FingerprintingConfiguration.FingerprintLength;
int height = param.FingerprintingConfiguration.LogBins;
imageService.GetImageForFingerprints(fingerprints, width, height, 2).Save(name + "_fingerprints.png");
}
#endif
Mirage.Dbg.WriteLine("GetFingerprintSignatures Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return fingerprints;
}
/// <summary>
/// Apply internal DCT and Mel Filterbands utilising the Comirva Matrix methods
/// </summary>
/// <param name="m">matrix (stftdata)</param>
/// <returns>matrix mel scaled and dct'ed</returns>
public Matrix ApplyMelScaleDCTComirva(ref Matrix m)
{
Mirage.DbgTimer t = new Mirage.DbgTimer();
t.Start();
// 4. Mel Scale Filterbank
// Mel-frequency is proportional to the logarithm of the linear frequency,
// reflecting similar effects in the human's subjective aural perception)
m = filterWeights * m;
// 5. Take Logarithm
// to db
double log10 = 20 * (1 / Math.Log(10)); // log for base 10 and scale by factor 10
m.ThrunkAtLowerBoundary(1);
m.LogEquals();
m *= log10;
// 6. DCT (Discrete Cosine Transform)
m = dct * m;
Mirage.Dbg.WriteLine("mfcc (MfccMirage-ComirvaWay) Execution Time: " + t.Stop().TotalMilliseconds + " ms");
return m;
}
