/// <summary>
/// Computes a Scms model from the MFCC representation of a song.
/// </summary>
/// <param name="mfcc">Comirva.Audio.Util.Maths.Matrix mfcc</param>
/// <returns></returns>
public static Scms GetScmsNoInverse(Comirva.Audio.Util.Maths.Matrix mfccs, string name)
{
DbgTimer t = new DbgTimer();
t.Start();
Comirva.Audio.Util.Maths.Matrix mean = mfccs.Mean(2);
#if DEBUG
if (Analyzer.DEBUG_INFO_VERBOSE)
{
if (Analyzer.DEBUG_OUTPUT_TEXT)
{
mean.WriteText(name + "_mean.txt");
}
mean.DrawMatrixGraph(name + "_mean.png");
}
#endif
// Covariance
Comirva.Audio.Util.Maths.Matrix covarMatrix = mfccs.Cov(mean);
#if DEBUG
if (Analyzer.DEBUG_INFO_VERBOSE)
{
if (Analyzer.DEBUG_OUTPUT_TEXT)
{
covarMatrix.WriteText(name + "_covariance.txt");
}
covarMatrix.DrawMatrixGraph(name + "_covariance.png");
}
#endif
Comirva.Audio.Util.Maths.Matrix covarMatrixInv = new Comirva.Audio.Util.Maths.Matrix(covarMatrix.Rows, covarMatrix.Columns);
// Store the Mean, Covariance, Inverse Covariance in an optimal format.
int dim = mean.Rows;
Scms s = new Scms(dim);
int l = 0;
for (int i = 0; i < dim; i++)
{
s.mean[i] = (float)mean.MatrixData[i][0];
for (int j = i; j < dim; j++)
{
s.cov[l] = (float)covarMatrix.MatrixData[i][j];
s.icov[l] = (float)covarMatrixInv.MatrixData[i][j];
l++;
}
}
Dbg.WriteLine("GetScmsNoInverse - Execution Time: {0} ms", t.Stop().TotalMilliseconds);
return(s);
}
/// <summary>
/// Computes a Scms model from the MFCC representation of a song.
/// </summary>
/// <param name="mfcc">Comirva.Audio.Util.Maths.Matrix mfcc</param>
/// <returns></returns>
public static Scms GetScmsNoInverse(Comirva.Audio.Util.Maths.Matrix mfccs, string name) {
DbgTimer t = new DbgTimer();
t.Start();
Comirva.Audio.Util.Maths.Matrix mean = mfccs.Mean(2);
#if DEBUG
if (Analyzer.DEBUG_INFO_VERBOSE) {
if (Analyzer.DEBUG_OUTPUT_TEXT) mean.WriteText(name + "_mean.txt");
mean.DrawMatrixGraph(name + "_mean.png");
}
#endif
// Covariance
Comirva.Audio.Util.Maths.Matrix covarMatrix = mfccs.Cov(mean);
#if DEBUG
if (Analyzer.DEBUG_INFO_VERBOSE) {
if (Analyzer.DEBUG_OUTPUT_TEXT) covarMatrix.WriteText(name + "_covariance.txt");
covarMatrix.DrawMatrixGraph(name + "_covariance.png");
}
#endif
Comirva.Audio.Util.Maths.Matrix covarMatrixInv = new Comirva.Audio.Util.Maths.Matrix(covarMatrix.Rows, covarMatrix.Columns);
// Store the Mean, Covariance, Inverse Covariance in an optimal format.
int dim = mean.Rows;
Scms s = new Scms(dim);
int l = 0;
for (int i = 0; i < dim; i++) {
s.mean[i] = (float) mean.MatrixData[i][0];
for (int j = i; j < dim; j++) {
s.cov[l] = (float) covarMatrix.MatrixData[i][j];
s.icov[l] = (float) covarMatrixInv.MatrixData[i][j];
l++;
}
}
Dbg.WriteLine("GetScmsNoInverse - Execution Time: {0} ms", t.Stop().TotalMilliseconds);
return s;
}
/// <summary>
/// Computes a Scms model from the MFCC representation of a song.
/// </summary>
/// <param name="mfcc">Comirva.Audio.Util.Maths.Matrix mfcc</param>
/// <returns></returns>
public static Scms GetScms(Comirva.Audio.Util.Maths.Matrix mfccs, string name)
{
DbgTimer t = new DbgTimer();
t.Start();
Comirva.Audio.Util.Maths.Matrix mean = mfccs.Mean(2);
#if DEBUG
if (Analyzer.DEBUG_INFO_VERBOSE)
{
if (Analyzer.DEBUG_OUTPUT_TEXT)
{
mean.WriteText(name + "_mean.txt");
}
mean.DrawMatrixGraph(name + "_mean.png");
}
#endif
// Covariance
Comirva.Audio.Util.Maths.Matrix covarMatrix = mfccs.Cov(mean);
#if DEBUG
if (Analyzer.DEBUG_INFO_VERBOSE)
{
if (Analyzer.DEBUG_OUTPUT_TEXT)
{
covarMatrix.WriteText(name + "_covariance.txt");
}
covarMatrix.DrawMatrixGraph(name + "_covariance.png");
}
#endif
// Inverse Covariance
Comirva.Audio.Util.Maths.Matrix covarMatrixInv;
try {
covarMatrixInv = covarMatrix.InverseGausJordan();
} catch (Exception) {
Dbg.WriteLine("MatrixSingularException - Scms failed!");
return(null);
}
#if DEBUG
if (Analyzer.DEBUG_INFO_VERBOSE)
{
if (Analyzer.DEBUG_OUTPUT_TEXT)
{
covarMatrixInv.WriteAscii(name + "_inverse_covariance.ascii");
}
covarMatrixInv.DrawMatrixGraph(name + "_inverse_covariance.png");
}
#endif
// Store the Mean, Covariance, Inverse Covariance in an optimal format.
int dim = mean.Rows;
Scms s = new Scms(dim);
int l = 0;
for (int i = 0; i < dim; i++)
{
s.mean[i] = (float)mean.MatrixData[i][0];
for (int j = i; j < dim; j++)
{
s.cov[l] = (float)covarMatrix.MatrixData[i][j];
s.icov[l] = (float)covarMatrixInv.MatrixData[i][j];
l++;
}
}
Dbg.WriteLine("Compute Scms - Execution Time: {0} ms", t.Stop().TotalMilliseconds);
return(s);
}