Implement a Trigram Tagger for Apertium and support-tools for training it

by Zaid Md. Abdul Wahab Sheikh for The Apertium Project

To implement the the part-of-speech tagger using 2nd order hidden Markov model and Viterbi algorithm, and the various training algorithms: maximum likelihood estimate (MLE), Kupiec's method, Baum-Welch expectation maximization, Parameter smoothing (state-to-state transition and emission probabilities) Tools to train the trigram tagger based on both source and target language information. Integrate Baum-Welch and supervised methods implemented in att-tools into Apertium bigram tagger.