protected internal virtual Pool createSenonePool(float distFloor, float varianceFloor)
{
Pool pool = new Pool("senones");
int num = this.meansPool.size();
int num2 = this.variancePool.size();
int gauPerState = this.mixtureWeights.getGauPerState();
int statesNum = this.mixtureWeights.getStatesNum();
int streamsNum = this.mixtureWeights.getStreamsNum();
int num3 = 0;
this.logger.fine(new StringBuilder().append("Senones ").append(statesNum).toString());
this.logger.fine(new StringBuilder().append("Gaussians Per Senone ").append(gauPerState).toString());
this.logger.fine(new StringBuilder().append("Means ").append(num).toString());
this.logger.fine(new StringBuilder().append("Variances ").append(num2).toString());
if (!Sphinx3Loader.assertionsDisabled && gauPerState <= 0)
{
throw new AssertionError();
}
if (!Sphinx3Loader.assertionsDisabled && num2 != statesNum * gauPerState)
{
throw new AssertionError();
}
if (!Sphinx3Loader.assertionsDisabled && num != statesNum * gauPerState)
{
throw new AssertionError();
}
float[][] meanTransformationMatrix = (this.meanTransformationMatrixPool != null) ? ((float[][])this.meanTransformationMatrixPool.get(0)) : ((float[][])null);
float[] meanTransformationVector = (this.meanTransformationVectorPool != null) ? ((float[])this.meanTransformationVectorPool.get(0)) : null;
float[][] varianceTransformationMatrix = (this.varianceTransformationMatrixPool != null) ? ((float[][])this.varianceTransformationMatrixPool.get(0)) : ((float[][])null);
float[] varianceTransformationVector = (this.varianceTransformationVectorPool != null) ? ((float[])this.varianceTransformationVectorPool.get(0)) : null;
for (int i = 0; i < statesNum; i++)
{
MixtureComponent[] array = new MixtureComponent[gauPerState * streamsNum];
for (int j = 0; j < gauPerState; j++)
{
MixtureComponent[] array2 = array;
int num4 = j;
array2[num4] = new MixtureComponent((float[])this.meansPool.get(num3), meanTransformationMatrix, meanTransformationVector, (float[])this.variancePool.get(num3), varianceTransformationMatrix, varianceTransformationVector, distFloor, varianceFloor);
num3++;
}
GaussianMixture o = new GaussianMixture(this.mixtureWeights, array, i);
pool.put(i, o);
}
return(pool);
}
private Pool createSenonePool(float num, float num2)
{
Pool pool = new Pool("senones");
int num3 = this.meansPool.size();
int num4 = this.variancePool.size();
int gauPerState = this.mixtureWeights.getGauPerState();
int statesNum = this.mixtureWeights.getStatesNum();
int num5 = 0;
this.logger.fine(new StringBuilder().append("NG ").append(gauPerState).toString());
this.logger.fine(new StringBuilder().append("NS ").append(statesNum).toString());
this.logger.fine(new StringBuilder().append("NMNS ").append(num3).toString());
this.logger.fine(new StringBuilder().append("NMNS ").append(num4).toString());
if (!HTKLoader.assertionsDisabled && gauPerState <= 0)
{
throw new AssertionError();
}
if (!HTKLoader.assertionsDisabled && num4 != statesNum * gauPerState)
{
throw new AssertionError();
}
if (!HTKLoader.assertionsDisabled && num3 != statesNum * gauPerState)
{
throw new AssertionError();
}
float[][] meanTransformationMatrix = (this.meanTransformationMatrixPool != null) ? ((float[][])this.meanTransformationMatrixPool.get(0)) : ((float[][])null);
float[] meanTransformationVector = (this.meanTransformationVectorPool != null) ? ((float[])this.meanTransformationVectorPool.get(0)) : null;
float[][] varianceTransformationMatrix = (this.varianceTransformationMatrixPool != null) ? ((float[][])this.varianceTransformationMatrixPool.get(0)) : ((float[][])null);
float[] varianceTransformationVector = (this.varianceTransformationVectorPool != null) ? ((float[])this.varianceTransformationVectorPool.get(0)) : null;
for (int i = 0; i < statesNum; i++)
{
MixtureComponent[] array = new MixtureComponent[gauPerState];
for (int j = 0; j < gauPerState; j++)
{
MixtureComponent[] array2 = array;
int num6 = j;
array2[num6] = new MixtureComponent((float[])this.meansPool.get(num5), meanTransformationMatrix, meanTransformationVector, (float[])this.variancePool.get(num5), varianceTransformationMatrix, varianceTransformationVector, num, num2);
num5++;
}
GaussianMixture o = new GaussianMixture(this.mixtureWeights, array, i);
pool.put(i, o);
}
return(pool);
}
