public virtual ArrayList cluster(ArrayList features)
{
ArrayList arrayList = new ArrayList();
Array2DRowRealMatrix array2DRowRealMatrix = this.ArrayToRealMatrix(features, features.size());
LinkedList allChangingPoints = this.getAllChangingPoints(array2DRowRealMatrix);
Iterator iterator = allChangingPoints.iterator();
int num = ((Integer)iterator.next()).intValue();
Array2DRowRealMatrix array2DRowRealMatrix2;
while (iterator.hasNext())
{
int num2 = ((Integer)iterator.next()).intValue();
Segment s = new Segment(num * 10, (num2 - num) * 10);
array2DRowRealMatrix2 = (Array2DRowRealMatrix)array2DRowRealMatrix.getSubMatrix(num, num2 - 1, 0, 12);
arrayList.add(new SpeakerCluster(s, array2DRowRealMatrix2, SpeakerIdentification.getBICValue(array2DRowRealMatrix2)));
num = num2;
}
int num3 = arrayList.size();
new Array2DRowRealMatrix(num3, num3);
array2DRowRealMatrix2 = this.updateDistances(arrayList);
for (;;)
{
double num4 = (double)0f;
int num5 = -1;
int num6 = -1;
for (int i = 0; i < num3; i++)
{
for (int j = 0; j < num3; j++)
{
if (i != j)
{
num4 += array2DRowRealMatrix2.getEntry(i, j);
}
}
}
num4 /= (double)(num3 * (num3 - 1) * 4);
for (int i = 0; i < num3; i++)
{
for (int j = 0; j < num3; j++)
{
if (array2DRowRealMatrix2.getEntry(i, j) < num4 && i != j)
{
num4 = array2DRowRealMatrix2.getEntry(i, j);
num5 = i;
num6 = j;
}
}
}
if (num5 == -1)
{
break;
}
((SpeakerCluster)arrayList.get(num5)).mergeWith((SpeakerCluster)arrayList.get(num6));
this.updateDistances(arrayList, num5, num6, array2DRowRealMatrix2);
arrayList.remove(num6);
num3 += -1;
}
return(arrayList);
}
public static void testSpeakerIdentification(string inputFile)
{
FileInputStream stream = new FileInputStream(inputFile);
ArrayList speakers = new SpeakerIdentification().cluster(stream);
Tester.printIntervals(speakers);
Tester.printSpeakerIntervals(speakers, inputFile);
}
internal virtual double getLikelihoodRatio(double num, int num2, Array2DRowRealMatrix array2DRowRealMatrix)
{
int num3 = 13;
double num4 = 0.5 * ((double)num3 + 0.5 * (double)num3 * (double)(num3 + 1)) * java.lang.Math.log((double)array2DRowRealMatrix.getRowDimension()) * 2.0;
int rowDimension = array2DRowRealMatrix.getRowDimension();
int columnDimension = array2DRowRealMatrix.getColumnDimension();
Array2DRowRealMatrix mat = (Array2DRowRealMatrix)array2DRowRealMatrix.getSubMatrix(0, num2 - 1, 0, columnDimension - 1);
Array2DRowRealMatrix mat2 = (Array2DRowRealMatrix)array2DRowRealMatrix.getSubMatrix(num2, rowDimension - 1, 0, columnDimension - 1);
double num5 = SpeakerIdentification.getBICValue(mat);
double num6 = SpeakerIdentification.getBICValue(mat2);
return(num - num5 - num6 - num4);
}
internal virtual double computeDistance(SpeakerCluster speakerCluster, SpeakerCluster speakerCluster2)
{
int rowDimension = speakerCluster.getFeatureMatrix().getRowDimension() + speakerCluster2.getFeatureMatrix().getRowDimension();
int columnDimension = speakerCluster.getFeatureMatrix().getColumnDimension();
Array2DRowRealMatrix array2DRowRealMatrix = new Array2DRowRealMatrix(rowDimension, columnDimension);
array2DRowRealMatrix.setSubMatrix(speakerCluster.getFeatureMatrix().getData(), 0, 0);
array2DRowRealMatrix.setSubMatrix(speakerCluster2.getFeatureMatrix().getData(), speakerCluster.getFeatureMatrix().getRowDimension(), 0);
double num = SpeakerIdentification.getBICValue(array2DRowRealMatrix);
double num2 = 13.0;
double num3 = 0.5 * (num2 + 0.5 * num2 * (num2 + (double)1f)) * java.lang.Math.log((double)array2DRowRealMatrix.getRowDimension()) * 2.0;
return(num - speakerCluster.getBicValue() - speakerCluster2.getBicValue() - num3);
}
private int getPoint(int num, int num2, int num3, Array2DRowRealMatrix array2DRowRealMatrix)
{
double num4 = double.NegativeInfinity;
int columnDimension = array2DRowRealMatrix.getColumnDimension();
int num5 = 0;
Array2DRowRealMatrix array2DRowRealMatrix2 = (Array2DRowRealMatrix)array2DRowRealMatrix.getSubMatrix(num, num + num2 - 1, 0, columnDimension - 1);
double num6 = SpeakerIdentification.getBICValue(array2DRowRealMatrix2);
for (int i = 14; i < num2 - 13; i += num3)
{
double num7 = this.getLikelihoodRatio(num6, i, array2DRowRealMatrix2);
if (num7 > num4)
{
num4 = num7;
num5 = i;
}
}
if (num4 < (double)0f)
{
num5 = int.MinValue;
}
return(num5 + num);
}
public virtual void mergeWith(SpeakerCluster target)
{
if (target == null)
{
throw new NullPointerException();
}
Iterator iterator = target.segmentSet.iterator();
while (iterator.hasNext())
{
if (!this.addSegment((Segment)iterator.next()).booleanValue())
{
[email protected]("Something doesn't work in mergeWith method, Cluster class");
}
}
int rowDimension = this.featureMatrix.getRowDimension() + target.getFeatureMatrix().getRowDimension();
int columnDimension = this.featureMatrix.getColumnDimension();
Array2DRowRealMatrix array2DRowRealMatrix = new Array2DRowRealMatrix(rowDimension, columnDimension);
array2DRowRealMatrix.setSubMatrix(this.featureMatrix.getData(), 0, 0);
array2DRowRealMatrix.setSubMatrix(target.getFeatureMatrix().getData(), this.featureMatrix.getRowDimension(), 0);
this.bicValue = SpeakerIdentification.getBICValue(array2DRowRealMatrix);
this.featureMatrix = new Array2DRowRealMatrix(array2DRowRealMatrix.getData());
}
