Lecture 25 (28/05/2020, Google meet, 3 hours): machine translation and homework 3

Introduction to machine translation (MT) and history of MT. Overview of statistical MT. The EM algorithm for word alignment in SMT. Beam search for decoding. Introduction to neural machine translation: the encoder-decoder neural architecture; back translation; byte pair encoding. The BLEU evaluation score. Performances and recent improvements. Neural MT: the encoder-decoder architecture; advantages; results. Attention in NMT. Unsupervised machine translation. MASS.

End of the course!