public void RunEMTraining()
{
IBMModel1 model = new IBMModel1();
List <EMTrainingRecord> training_corpus = new List <EMTrainingRecord>();
EnglishTokenizer tokenizer_output = new EnglishTokenizer();
FrenchTokenizer tokenizer_input = new FrenchTokenizer();
//training_corpus_from_f_to_e.Add(new EMTrainingRecord()
//{
// InputLang=tokenizer_input.Tokenize("[Some French Sentence]"),
// OutputLang = tokenizer_output.Tokenize("[Some English Sentence]"),
//});
//...
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 InitializeIBMModels(IBMModel2 model_f_to_e, IBMModel2 model_e_to_f, IEnumerable <EMTrainingRecord> training_corpus_f_to_e, int maxIterations)
{
EMTrainingMethod.Train(model_f_to_e, model_e_to_f, training_corpus_f_to_e, maxIterations);
}
