Schedule and Readings

Schedule is subject to change

Week	Date	Topic	Readings (=optional)
1	Jan 19	Introduction	Lewis-Kraus, Is Translation an Art or a Math Problem?
1	Jan 21	Hands-on with Moses	Koehn, Preface Koehn, Errata for Chapter 1 Koehn, Chapter 1
2	Jan 26	Approaches to Machine Translation	Knight, Automating Knowledge Acquisition for Machine Translation Weaver, Translation Kay, Translation
2	Jan 28	Words, Sentences, Corpora	Koehn, Errata for Chapter 2 Koehn, Chapter 2
3	Feb 02	Probability and Statistics	Koehn, Errata for Chapter 3 Koehn, Chapter 3
3	Feb 04	Lexical Translation Models: Part 1	Schwartz, Video Lecture (The Noisy Channel Model) Koehn, Errata for Chapter 4 Koehn, Chapter 4 Knight, A Tutorial MT Workbook Collins, Statistical Machine Translation: IBM Models 1 and 2 Brown et al., A Statistical Approach to Machine Translation
4	Feb 09	Lexical Translation Models: Part 2	Brown et al., The Mathematics of Statical Machine Translation: Parameter Estimation Vogel and Ney, HMM-based word alignment in statistical translation Liang et al., Alignment by Agreement
4	Feb 11	Language Models	Koehn, Errata for Chapter 7 Koehn, Chapter 7 Google researchers, Large Language Models in Machine Translation Pauls and Klein, Large-Scale Syntactic Language Modeling with Treelets Goodman, A Bit of Progress in Language Modeling Jurafsky, Coursera Lecture
5	Feb 16	Phrase-based Machine Translation	Koehn, Errata for Chapter 5 Koehn, Chapter 5 Koehn, Och and Marcu, Statistical Phrase-Based Translation
5	Feb 18	Phrase-based Machine Translation part 2	Koehn, Errata for Chapter 6 Koehn, Chapter 6 Och and Ney, The Alignment Template Approach to Statistical Machine Translation
6	Feb 23	DARPA LORELEI PI Meeting
6	Feb 25	DARPA LORELEI PI Meeting
7	Mar 01	Evaluating translation quality	Koehn, Errata for Chapter 8 Koehn, Chapter 8 Papineni, Roukos, Ward and Zhu, BLEU: a Method for Automatic Evaluation of Machine Translation
7	Mar 03	Discriminative training	Koehn, Errata for Chapter 9 Koehn, Chapter 9 Och and Ney, Discriminative Training And Maximum Entropy Models For Statistical Machine Translation Och, Minimum Error Rate Training In Statistical Machine Translation
8	Mar 08	Re-ordering for phrase-based translation	Koehn, Errata for Chapters 5 and 10 Koehn, Chapter 5.4.2 and 10.3 Koehn et al, Description of lexialized reordering in Edinburgh System Description for the 2005 IWSLT Speech Translation Evaluation Collins, Koehn, Kucerova, Clause Restructuring for Statistical Machine Translation Mark Twain, The Awful German Language
8	Mar 10
9	Mar 15	Hands-on with Moses EMS
9	Mar 17	Informal project updates
10	Mar 22	Spring Break
10	Mar 24	Spring Break
11	Mar 29
11	Mar 31	Morphology and Factors	Koehn, Errata for Chapter 10 Koehn, Chapter 10.2 and 10.5
12	Apr 05	WMT Shared Task
12	Apr 07	WMT Shared Task
13	Apr 12	WMT Shared Task
13	Apr 14	Synchronous Grammars	Koehn, Errata for Chapter 11 Koehn, Chapter 11 David Chiang, Hierarchical Phrase-Based Translation Heidi Fox, Phrasal Cohesion and Statistical Machine Translation
14	Apr 18	WMT Shared Task test set distributed
14	Apr 19	Decoding and Inference with Syntactic Translation Models	Dekai Wu, Stochastic Inversion Transduction Grammars and Bilingual Parsing of Parallel Corpora Stu Shieber, Yves Schabes, and Ferndando Pereira, Principles and Implementation of Deductive Parsing Dan Klein and Chris Manning, Parsing and Hypergraphs
14	Apr 21	Harvesting Parallel Documents from the Web	Philip Resnik and Noah Smith, The Web as a Parallel Corpus Jakob Uszkoreit, Jay Ponte, Ashok Popat, and Moshe Dubiner, Large Scale Parallel Document Mining for Machine Translation Ashish Venugopal, Jakob Uszkoreit, David Talbot, Franz Och, Juri Ganitkevitch, Watermarking the Outputs of Structured Prediction with an application in Statistical Machine Translation
15	Apr 24	WMT Shared Task submission deadline
15	Apr 26	Crowdsourcing translation	Omar Zaidan and Chris Callison-Burch, Crowdsourcing Translation: Professional Quality from Non-Professionals. Chris Callison-Burch, Fast, Cheap, and Creative: Evaluating Translation Quality Using Amazon's Mechanical Turk Ellie Pavlick, Matt Post, Ann Irvine, Dmitry Kachaev, and Chris Callison-Burch, The Language Demographics of Amazon Mechanical Turk
16	May 05	Course wrap-up

Many of the lectures from this course were adapted (or stolen wholesale) from Chris Dyer, Adam Lopez, Matt Post, and Chris Callison-Burch. I am grateful to them for making their lecture materials available.