/**
* Calculates probability p = w[1]*p[1] + w[2]*p[2] + ... (in log domain)
*
* @see
* edu.cmu.sphinx.linguist.language.ngram.LanguageModel#getProbability(edu.cmu.sphinx.linguist.WordSequence)
*/
public float getProbability(WordSequence wordSequence) {
float prob = 0;
for (int i = 0; i < numberOfLanguageModels; i++) {
float p = weights[i] + (languageModels.get(i)).getProbability(wordSequence);
if (i == 0) {
prob = p;
} else {
prob = logMath.addAsLinear(prob, p);
}
}
return prob;
}
public float calculateScore(Data feature) {
if (feature instanceof DoubleData) {
System.err.println("DoubleData conversion required on mixture level!");
}
float[] featureVector = FloatData.toFloatData(feature).getValues();
float logTotal = LogMath.getLogZero();
for (int i = 0; i < mixtureComponents.length; i++) {
// In linear form, this would be:
//
// Total += Mixture[i].score * MixtureWeight[i]
logTotal =
logMath.addAsLinear(
logTotal, mixtureComponents[i].getScore(featureVector) + logMixtureWeights[i]);
}
return logTotal;
}
