public void RunEMTraining()
{
IBMModel2 model = new IBMModel2();
List <EMTrainingRecord> training_corpus = new List <EMTrainingRecord>();
EnglishTokenizer tokenizer_output = new EnglishTokenizer();
FrenchTokenizer tokenizer_input = new FrenchTokenizer();
EMTrainingMethod.Train(model, training_corpus, 20);
string sentence_input = "[Some French Sentence]";
string sentence_output = "[Some English Sentence]";
string[] input_lang = tokenizer_input.Tokenize(sentence_input);
string[] output_lang = tokenizer_output.Tokenize(sentence_output);
int[] alignment = model.GetAlignment(input_lang, output_lang);
Dictionary <int, string> output_mapping = new Dictionary <int, string>();
int m_input_len = input_lang.Length;
for (int j = 0; j < m_input_len; ++j)
{
int a_j = alignment[j];
string output_word = output_lang[a_j];
output_mapping[a_j] = output_word;
}
List <int> output_sentence_index_list = output_mapping.Keys.ToList();
output_sentence_index_list.Sort();
string[] predicted_output_lang = new string[output_sentence_index_list.Count];
for (int i = 0; i < predicted_output_lang.Length; ++i)
{
predicted_output_lang[i] = output_mapping[output_sentence_index_list[i]];
}
Console.WriteLine("Original French Sentence: {0}", sentence_input);
Console.WriteLine("Predicted English Translation: {0}", string.Join(" ", predicted_output_lang));
}
public void GetAlignmentMatrix(IBMModel2 model_f_to_e, IBMModel2 model_e_to_f, string[] ws_f, string[] ws_e, out Dictionary <int, int> intersection_points)
{
int[] alignment_f_to_e = model_f_to_e.GetAlignment(ws_f, ws_e);
int[] alignment_e_to_f = model_e_to_f.GetAlignment(ws_e, ws_f);
int m_f_len = alignment_f_to_e.Length;
int l_e_len = alignment_e_to_f.Length;
intersection_points = new Dictionary <int, int>();
int[][] alignment_matrix = new int[m_f_len][];
for (int j = 0; j < m_f_len; ++j)
{
alignment_matrix[j] = new int[l_e_len];
for (int i = 0; i < l_e_len; ++i)
{
if (alignment_f_to_e[j] == i && alignment_e_to_f[i] == j)
{
intersection_points[j] = i;
alignment_matrix[j][i] = 1;
}
}
}
}
