//Load language model from specific file
public void LoadLM(string strFileName)
{
//Load prob & back off values
StreamReader srLM = new StreamReader(strFileName + ".prob");
BinaryReader br = new BinaryReader(srLM.BaseStream);
lm_prob = new VarBigArrayNoCMP <NGram>(1024000);
long index = 0;
try
{
while (true)
{
NGram ngram = new NGram();
ngram.prob = br.ReadSingle();
ngram.bow = br.ReadSingle();
lm_prob[index] = ngram;
index++;
}
}
catch (EndOfStreamException err)
{
br.Close();
}
daSearch.Load(strFileName + ".da");
}
private int lm_ngram_prob(string strText, int start, int end, ref double probability)
{
NGram lm_ngram = new NGram();
// get the longest ngram conditional prob in LM
int j;
for (j = start; j <= end; j++)
{
string words = GenerateNGram(strText, j);
int offset = daSearch.SearchByPerfectMatch(words);
if (offset >= 0)
{
lm_ngram = lm_prob[offset];
break;
}
}
if (j > end)
{
return(1);// OOV
}
else if (j == start)
{
probability = lm_ngram.prob;
return(0); // exact ngram in LM
}
double prob = lm_ngram.prob;
double bow = 0;
// get bows starting from the longest ngram prob to the original ngram
// exclude the last word, set temp buffer end
string[] ngrams = strText.Split();
strText = String.Join(" ", ngrams, 0, ngrams.Length - 1);
for (j--; j >= start; j--)
{
string words = GenerateNGram(strText, j);
int offset = daSearch.SearchByPerfectMatch(words);
if (offset < 0)
{
break;
}
bow += lm_prob[offset].bow;
}
probability = prob + bow;
return(0);
}
