Machine Translation

Lectures

For the time and place of lectures, check here.

No.DateLecturerTopicReading
116.1 OsborneIntroduction-
219.1 OsborneHistory (rule-based systems, up to 1990s)Hutchins
323.1 OsborneEvaluation (automatic and subjective) Koehn Chapter 8; Papineni et al
426.1 Osborne Data (Parallel corpora, comparable corpora) Koehn pp 44 -- 47, Gale and Church, Munteau and Marcu
5 30.1OsborneLanguage ModelsKoehn Chapter 7, Google LM paper, Randomised LM paper
66.2 HaddowWord-based models 1 (IBM Model 1, EM) Koehn Chapter 4: Section 4.1, 4.2
79.2 HaddowIBM Models in Practice: Alignment and Symmetrisation Koehn Chapter 4: Section 4.4.1, 4.5
813.2 HaddowPhrase-based models 1 (Training) Koehn Chapter 5
916.2 HaddowPhrase-based models 2 (Decoding) Koehn Chapter 6
10 27.2 HaddowPhrase-based models 3 (Tuning) Koehn Chapter 9: Section 9.3, Hopkins and May
111.3 HaddowReordering Koehn Chapter 10: section 10.3, Birch et al.
125.3 HaddowDomain Adaptation Moore, Foster
138.3 OsborneSyntax 1 (Hiero)Koehn chaper 11, Hiero
1412.3 OsborneDecoding for SyntaxKoehn chaper 11, Hiero, Suffix arrays
1515.3 OsborneSyntax 2 (Linguistically informed grammars) What's in a rule?, Re-ranking
1619.3 OsborneLarge-scale discriminative translationBlunsom et al 08a


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