Statistical Machine Translation

Date	Topic	Readings (starred=graduate level)
Sep 05	Introduction	Koehn, Chapter 1.2 Weaver (1949), Translation Kay, Translation
Sep 07	Basics in Language and Probability	Koehn, Chapter 2.1 and 3
Sep 12	Language Models	Koehn, Chapter 7
Sep 14	IBM Model 1 and the EM Algorithm	Koehn, Chapter 4.1-4.2 Knight (1997), Automating Knowledge Acquisition for Machine Translation
Sep 19	Phrase-Based Models	Koehn, Chapter 5 Durrani et al. (2013), Can Markov Models Over Minimal Translation Units Help Phrase-Based SMT?
Sep 21	Decoding (Demo)	Koehn, Chapter 6 Heafield et al. (2014), Faster Phrase-Based Decoding by Refining Feature State
Sep 26	Evaluation	Koehn, Chapter 8 Graham et al. (2014), Is Machine Translation Getting Better over Time?
Sep 28	Tuning	Koehn, Chapter 9.1-9.3
Oct 03	Introduction to Neural Networks	Koehn (2017), Neural Machine Translation, Chapter 2 Makin (2006), Backpropagation LeCun et al. (1998), Efficient BackProp Srivastava et al. (2014), Dropout - A Simple Way to Prevent Neural Networks from Overfitting
Oct 05	Computation Graphs	Koehn (2017), Neural Machine Translation, Chapter 3 Tensorflow, Neural network online demo
Oct 10	Neural Language Models	Koehn (2017), Neural Machine Translation, Chapter 4 Bengio et al. (2002), A Neural Probabilistic Language Model Tomas Mikolov (2012), Statistical Language Models Based on Neural Networks, Chapter 3 Karpathy et al. (2015), Visualizing and Understanding Recurrent Networks
Oct 12	Neural Translation Models I	Koehn (2017), Neural Machine Translation, Chapter 5 Bahdanau et al. (2015), Neural Machine Translation by Jointly Learning to Align and Translate
Oct 17	Neural Translation Models II - Refinements	Koehn (2017), Neural Machine Translation, Chapter 6
Oct 19	(no class)
Oct 24	Neural Translation Models III - Challenges and Alternatives	Koehn (2017), Neural Machine Translation, Chapter 7 and 8 Vaswani et al. (2017), Attention Is All You Need Gehring et al. (2017), Convolutional Sequence to Sequence Learning
Oct 26	Corpus Acquisition from the Internet	Uszkoreit et al. (2010), Large Scale Parallel Document Mining for Machine Translation Resnik and Smith (2003), The Web as a Parallel Corpus Buck and Heafield (2014), N-gram Counts and Language Models from the Common Crawl
Oct 31	Word Order	Koehn, Chapter 10.3 Genzel (2010), Automatically Learning Source-side Reordering Rules for Large Scale Machine Translation Bisazza and Federico (2010), Chunk-based Verb Reordering in VSO Sentences for Arabic-English Statistical Machine Translation
Nov 02	Morphology	Koehn, Chapter 10.2 Stymne et al. (2013), Generation of Compound Words in Statistical Machine Translation into Compounding Languages Fraser et al. (2012), Modeling Inflection and Word-Formation in SMT Chahuneau et al. (2013), Translating into Morphologically Rich Languages with Synthetic Phrases
Nov 04	Syntax-Based Models	Koehn, Chapter 11.1-11.2
Nov 09	Syntax-Based Decoding I	Koehn, Chapter 11.3
Nov 14	Syntax-Based Decoding II	Koehn, Chapter 11.3 Hopkins and Langmead (2010), SCFG Decoding Without Binarization Sennrich (2014), A CYK+ Variant for SCFG Decoding Without a Dot Chart
Nov 16	Semantics	Cook et al. (2011), The World Color Survey Database - History and Use Banarescu et al. (2013), Abstract Meaning Representation for Sembanking
Nov 28	Computer Aided Translation	Barrachina et al. (2009), Statistical Approaches to Computer-Assisted Translation Germann (2014), Dynamic Phrase Tables for Machine Translation in an Interactive Post-editing Scenario
Nov 30	Adaptation	Axelrod et al. (2011), Domain adaptation via pseudo in-domain data selection
Dec 05	(no class - work on final project)