private Pool <ISenone> CreateTiedSenonePool(float distFloor, float varianceFloor)
{
var pool = new Pool <ISenone>("senones");
var numMeans = MeansPool.Size;
var numVariances = VariancePool.Size;
var numGaussiansPerState = MixtureWeightsPool.GauPerState;
var numSenones = MixtureWeightsPool.StatesNum;
var numStreams = MixtureWeightsPool.StreamsNum;
this.LogInfo("Senones " + numSenones);
this.LogInfo("Gaussians Per State " + numGaussiansPerState);
this.LogInfo("Means " + numMeans);
this.LogInfo("Variances " + numVariances);
Debug.Assert(numGaussiansPerState > 0);
Debug.Assert(numVariances == _numBase * numGaussiansPerState * numStreams);
Debug.Assert(numMeans == _numBase * numGaussiansPerState * numStreams);
var meansTransformationMatrix = MeansTransformationMatrixPool == null ? null
: MeansTransformationMatrixPool.Get(0);
var meansTransformationVector = MeansTransformationVectorPool == null ? null
: MeansTransformationVectorPool.Get(0);
var varianceTransformationMatrix = VarianceTransformationMatrixPool == null ? null
: VarianceTransformationMatrixPool.Get(0);
var varianceTransformationVector = VarianceTransformationVectorPool == null ? null
: VarianceTransformationVectorPool.Get(0);
_phoneticTiedMixtures = new MixtureComponentSet[_numBase];
for (var i = 0; i < _numBase; i++)
{
var mixtureComponents = new List <PrunableMixtureComponent[]>();
for (var j = 0; j < numStreams; j++)
{
var featMixtureComponents = new PrunableMixtureComponent[numGaussiansPerState];
for (var k = 0; k < numGaussiansPerState; k++)
{
var whichGaussian = i * numGaussiansPerState * numStreams + j * numGaussiansPerState + k;
featMixtureComponents[k] = new PrunableMixtureComponent(
MeansPool.Get(whichGaussian),
meansTransformationMatrix, meansTransformationVector,
VariancePool.Get(whichGaussian),
varianceTransformationMatrix,
varianceTransformationVector, distFloor, varianceFloor, k);
}
mixtureComponents.Add(featMixtureComponents);
}
_phoneticTiedMixtures[i] = new MixtureComponentSet(mixtureComponents, _topGauNum);
}
for (var i = 0; i < numSenones; i++)
{
ISenone senone = new SetBasedGaussianMixture(MixtureWeightsPool, _phoneticTiedMixtures[Senone2Ci[i]], i);
pool.Put(i, senone);
}
return(pool);
}
private Pool createTiedSenonePool(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 streamsNum = this.mixtureWeights.getStreamsNum();
this.logger.fine(new StringBuilder().append("Senones ").append(statesNum).toString());
this.logger.fine(new StringBuilder().append("Gaussians Per State ").append(gauPerState).toString());
this.logger.fine(new StringBuilder().append("Means ").append(num3).toString());
this.logger.fine(new StringBuilder().append("Variances ").append(num4).toString());
if (!Sphinx3Loader.assertionsDisabled && gauPerState <= 0)
{
throw new AssertionError();
}
if (!Sphinx3Loader.assertionsDisabled && num4 != this.numBase * gauPerState * streamsNum)
{
throw new AssertionError();
}
if (!Sphinx3Loader.assertionsDisabled && num3 != this.numBase * gauPerState * streamsNum)
{
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;
this.phoneticTiedMixtures = new MixtureComponentSet[this.numBase];
for (int i = 0; i < this.numBase; i++)
{
ArrayList arrayList = new ArrayList();
for (int j = 0; j < streamsNum; j++)
{
PrunableMixtureComponent[] array = new PrunableMixtureComponent[gauPerState];
for (int k = 0; k < gauPerState; k++)
{
int id = i * gauPerState * streamsNum + j * gauPerState + k;
PrunableMixtureComponent[] array2 = array;
int num5 = k;
array2[num5] = new PrunableMixtureComponent((float[])this.meansPool.get(id), meanTransformationMatrix, meanTransformationVector, (float[])this.variancePool.get(id), varianceTransformationMatrix, varianceTransformationVector, num, num2, k);
}
arrayList.add(array);
}
this.phoneticTiedMixtures[i] = new MixtureComponentSet(arrayList, this.topGauNum);
}
for (int i = 0; i < statesNum; i++)
{
SetBasedGaussianMixture o = new SetBasedGaussianMixture(this.mixtureWeights, this.phoneticTiedMixtures[this.senone2ci[i]], i);
pool.put(i, o);
}
return(pool);
}