Friday, June 6, 2014

Lecture 12: Statistical Machine Translation

Introduction to Machine Translation. Rule-based vs. Statistical MT. Statistical MT: the noisy channel model. The language model and the translation model. The phrase-based translation model. Learning a model of training. Phrase-translation tables. Parallel corpora. Extracting phrases from word alignments. Word alignments

IBM models for word alignment. Many-to-one and many-to-many alignments. IBM model 1 and the HMM alignment model. Training the alignment models: the Expectation Maximization (EM) algorithm. Symmetrizing alignments for phrase-based MT: symmetrizing by intersection; the growing heuristic. Calculating the phrase translation table. Decoding: stack decoding. Evaluation of MT systems. BLEU. Log-linear models for MT.

Monday, June 2, 2014

Lecture 11: Homework 1 correction + homework Q&A + Combinatory Categorial Grammar (CCG)

Homework 1 correction. Q&A on the other two homeworks. Combinatory Categorial Grammar (CCG).


Lecture 10: NLP research at LCL, Sapienza