MACHINE TRANSLATIONLECTURESFor the time and place of lectures, check here.

No.	Date	Lecturer	Topic	Reading
1	13.1	Haddow	Introduction	-
2	16.1	Germann	History (rule-based systems, up to 1990s)	Banko and Brill, Halevy et al., Knight et al.
3	20.1	Haddow	Evaluation (automatic and subjective)	Koehn Chapter 8; Papineni et al, Callison-Burch et al.
4	23.1	Haddow	Data (Parallel corpora, comparable corpora)	Koehn pp 53 -- 57, Uszkoreit et al.
5	27.1	Haddow	Language Models	Koehn Chapter 7, Heafield et al.
6	30.1	Germann	Word-based models 1 (IBM Model 1, EM)	Koehn Chapter 4: Section 4.1, 4.2
7	3.2	Germann	IBM Models in Practice: Word-based Translation and Alignment Models	Koehn Chapter 4: Section 4.4.1, 4.5
	6.2	Haddow/Germann	Tutorial	Assignment Clarifications
8	10.2	Huck	Phrase-based models 1 (Training)	Koehn Chapter 5
9	13.2	Huck	Phrase-based models 2 (Decoding)	Koehn Chapter 6
10	24.2	Huck	Phrase-based models 3 (Tuning)	Koehn Chapter 9: Section 9.3, Hopkins and May
	27.2	Hoang/Huck	Tutorial
11	3.3	Huck	Reordering	Koehn Chapter 10: section 10.3, Birch et al.
12	6.3	Hoang	Syntax-based Models 1	Koehn chaper 11, Hiero
13	10.3	Hoang	Syntax-based Models 2	Synchronous Grammar Tutorial by D. Chiang
14	13.3	Hoang	More on Syntax-based MT	11001 New Features for SMT
14	17.3	Hoang	SMT of Spoken Language; Compressed Phrase Tables	TBD
16	20.3	Haddow	Domain Adaptation	Irvine et al., Sennrich
17	24.3	Germann	Guest lecture by Philipp Koehn: Computer-aided Translation	TBD