Syllabus

Subject to change as the term progresses.

Date	Topic	Readings (starred=graduate level)
Jan 15	Introduction	Koehn, chapter 1 Knight, Automating Knowledge Acquisition for Machine Translation Weaver, Translation Kay, Translation
Jan 20	Probability and Statistics	Koehn, chapters 3
Jan 22	Language Models	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
Jan 27	Lexical Translation Models: Part 1	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
Jan 29	Lexical Translation Models: Part 2	Koehn, chapter 4 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
Feb 03	Discriminative alignment models	Blunsom and Cohn, Discriminative Word Alignment with Conditional Random Fields Sutton and McCallum, An Introduction to Conditional Random Fields
Feb 05	Phrase-based Machine Translation	Koehn, chapter 5 Koehn, Och and Marcu, Statistical Phrase-Based Translation
Feb 10	Phrase-based Machine Translation part 2	Koehn, chapter 6 Och and Ney, The Alignment Template Approach to Statistical Machine Translation
Feb 12	Evaluating translation quality	Koehn, chapter 8 Papineni, Roukos, Ward and Zhu, BLEU: a Method for Automatic Evaluation of Machine Translation
Feb 17	Evaluating translation quality - part 2	Koehn, chapter 8 Callison-Burch, Fordyce, Koehn, Monz and Schroeder, (Meta-) Evaluation of Machine Translation
Feb 19	Discriminative training	Koehn, chapter 9 Och and Ney, Discriminative Training And Maximum Entropy Models For Statistical Machine Translation
Feb 24	Discriminative training - part 2	Koehn, chapter 9 Och, Minimum Error Rate Training In Statistical Machine Translation Hopkins and May, Tuning as Ranking
Feb 26	Re-ordering for phrase-based translation	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
Mar 03	Synchronous Grammars	Koehn, chapter 11 David Chiang, Hierarchical Phrase-Based Translation Heidi Fox, Phrasal Cohesion and Statistical Machine Translation
Mar 05	Class canceled because of snow (instead we held a Google Hangout discussing final project topics)
Mar 10	No class today (Spring Break)
Mar 12	No class today (Spring Break)
Mar 17	Decoding and Inference with Syntactic Translation Models	Koehn, chapter 11 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
Mar 19	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
Mar 24	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
Mar 26	Paraphrasing	Colin Bannard and Chris Callison-Burch, Paraphrasing with Bilingual Parallel Corpora Juri Ganitkevitch, Chris Callison-Burch, Courtney Napoles, and Benjamin Van Durme, Learning Sentential Paraphrases from Bilingual Parallel Corpora for Text-to-Text Generation Juri Ganitkevitch, Benjamin Van Durme and Chris Callison-Burch,, PPDB: The Paraprhase Database
Mar 31	Guest lecture by Liang Huang - CUNY Queens	Liang Huang, Kevin Knight, and Aravind Joshi, Statistical Syntax-Directed Translation with Extended Domain of Locality Haitao Mi, Liang Huang, and Qun Liu, Forest-Based Translation Haitao Mi and Liang Huang, Forest-based Translation Rule Extraction
Apr 02	Guest lecture by Wei Xu - Penn	Wei Xu, Alan Ritter, Chris Callison-Burch, William B. Dolan and Yangfeng Ji, Extracting Lexically Divergent Paraphrases from Twitter
Apr 07	No class today (Instructor will be giving a talk at Carnegie Mellon University)
Apr 09	Guest lecture by Matt Post (Johns Hopkins University HLTCOE)	Mark Hopkins and Jonathan May, Models of Translation Competitions Keisuke Sakaguchi, Matt Post, and Ben Van Durme, Efficient Elicitation of Annotations for Human Evaluation of Machine Translation
Apr 14	Translation without parallel corpora	Reinhard Rapp, Identifying Word Translations in Non-Parallel Texts Reinhard Rapp, Automatic identification of word translations from unrelated English and German corpora Charles Schafer and David Yarowsky, Inducing translation lexicons via diverse similarity measures and bridge languages Alex Klementiev, Ann Irvine, Chris Callison-Burch, and David Yarowsky,, Toward Statistical Machine Translation without Parallel Corpora
Apr 16	Guest lecture by Will Lewis (Microsoft Research) on the Skype speech-to-speech translation system. If you would like a copy of the slides, email CCB.
Apr 21	Christian Buck (PhD student at the University of Edinburgh)	Specia et. al, Estimating the sentence-level quality of machine translation systems Specia et. al, QuEst-A translation quality estimation framework Soricut and Echihabi, TrustRank: inducing trust in automatic translations via ranking Bach et. al, Goodnessk: a method for measuring machine translation confidence
Apr 23	Guest lecture by Kenneth Heafield (Bloomberg)	Kenneth Heafield, Mike Kaiser and Chris Manning, Faster Phrase-Based Decoding by Refining Feature State Kenneth Heafield, Philipp Koehn and Alon Lavie, Grouping Language Model Boundary Words to Speed K–Best Extraction from Hypergraphs
Apr 28	Course wrap-up

Many of the lectures from this course were adapted from Chris Dyer, Adam Lopez and Matt Post. I am grateful to them for making their lecture materials available.