The Machine Translation Reading Group at SSLI-LAB, UW-EE.

This reading group is part of SSLI-Lab, the Signal, Speech, and Language Interpretation Laboratory in the department of Electrical Engineering at the University of Washington. We conduct research on statistical speech and natural language processing, including machine translation.

Send mail to username katrin at ee.washington.edu if you would like to receive email announcements and reminders regarding upcoming meetings, or if you would like to lead a discussion (regardless of your department!).
While the list of papers below will give you something to choose from, it is far from exhaustive and you are encouraged to suggest other machine translation papers.

Discussions, Spring 2008

Topic	Readings	Date/Time/Location	Discussion leader	Slides / Notes
.	Yajuan Lu + Jin Huang + Qun Liu (Chinese Academy of Sciences) Improving Statistical Machine Translation Performance by Training Data Selection and Optimization (EMNLP 2007)	Mon, 02 Jun 4-5pm, EE-M306	Mei Yang	slides
.	Holiday, no MTRG	Mon, 26 May	.	.
Morphology	K. Toutanova + H. Suzuki + A. Ruopp (MSR) Applying Morphology Generation Models to Machine Translation (ACL 2008)	Mon, 19 May 4-5pm, EE-M306	amittai	slides
.	cancelled	Mon, 12 May	.	.
Text processing	Unicode and its discontents. Discussion on character encodings, and the practicalities (and hassles) of working with text.	Mon, 05 May 4-5pm, EE-M306	Jeremy Kahn	slides
Parsing	Y. W. Wong + R. J. Mooney (UT Austin), Generation by Inverting a Semantic Parser That Uses Statistical Machine Translation (HLT/NAACL 2007).	Mon, 28 Apr 4-5pm, EE-M306	Katrin Kirchhoff	.
Language Modeling	T. Brants + A. C. Popat + P. Xu + F. J. Och + J. Dean (Google), Large Language Models in Machine Translation (EMNLP 2007)	Mon, 21 Apr 4-5pm, EE-M306	Kevin Duh	.

Discussions, Winter 2008

Relevant Calls for papers

• statmt.org
• mt-archive.info
• URochester's conference and upcoming deadline list

Partial (and growing) Lists of Suggested Papers

Introductory/Classical Papers in Statistical MT

1. Chapter from Russell & Norvig's book " AI: A Modern Approach, 2nd Edition". The 2nd editions chapter on MT is very good.
2. Chapter on MT from Jurafsky & Martin's book "Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition"
3. A Statistical MT Tutorial Workbook, Kevin Knight, unpublished, August 1999 pdf link
4. P.F. Brown et al., A statistical approach to machine translation, Computational Linguistics, 16, 1990, 79-85 link
5. S. Della Pietra and M. Epstein and S. Roukos and T. Ward, Fertility models for statistical natural language understanding, Proceedings of ACL, 1997, 168-173 link
6. The Candide System for Machine Translation (1994), Adam L. Berger, Peter F. Brown, Stephen A. Della Pietra, Vincent J. Della Pietra, John R. Gillett, John D. Lafferty, Robert L. Mercer, Harry Printz, Lubos Ures link
7. P. F. Brown, S. A. Della Pietra, V. J. Della Pietra, and R. L. Mercer. The mathematics of statistical machine translation: Parameter estimation. Computational linguistics, 19:263--312, June 1993.link
8. Kenji Yamada's Intro to Statistical Machine Translation Notes link
9. Knight and Koehn HLT tutorial: "What's New in Statistical Machine Translation" link

1. K. Papineni and S. Roukos and T. Ward and W. Zhu, Bleu: a method for automatic evaluation of machine translation, 2001, IBM Research Report RC22176 link
2. Hovy E., King M. & Popescu-Belis A. (2002) - An Introduction to MT Evaluation. LREC 2002 Workshop "Machine Translation Evaluation: Human Evaluators Meet Automated Metrics", Las Palmas de Gran Canaria, Spain, p.1-7. link
3. Culy, Christopher and Riehemann, Susanne. 2003. The Limits of N-Gram Translation Evaluation Metrics. Proceedings of MT Summit IX. link
4. FEMTI, the Framework for Machine Translation Evaluation in ISLE, a structured repertoire of methods used to evaluate MT systems. link1 and link2
5. Automatic Evaluation of Machine Translation Quality Using N-gram Co-Occurrence Statistics, NIST document. link
6. A Novel String-to-String Distance Measure With Applications to Machine Translation Evaluation, by Leusch, Ueffing, and Ney. link
7. Orange: a Method for Evaluating Automatic Metrics for Machine Translation, by Lim and Och, Coling04, link

1. A Syntax-based Statistical Translation Model (2001) Kenji Yamada, Kevin Knight Meeting of the Association for Computational Linguistics link
2. Modeling with Structures in Statistical Machine Translation (1997) Ye-Yi Wang, Alex Waibel COLING-ACL link
3. Statistical Phrase-Based Translation, Philipp Koehn, Franz Josef Och, and Daniel Marcu, HLT/NAACL 2003 link
4. A phrase-based joint probability model for statistical machine translation, D. Marcu, Proceedings of EMNLP, 2002 link
5. Marcu, D. and Wong, W. (2002). A phrase-based, joint probability model for statistical machine translation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP.h
6. Och, F. J., Tillmann, C., and Ney, H. (1999). Improved alignment models for statistical machine translation. In Proc. of the Joint Conf. of Empirical Methods in Natural Language Processing and Very Large Corpora, pages 20-28. link
7. A Syntax-Based Statistical Translation Model" (K. Yamada and K. Knight), Proc. of the Conference of the Association for Computational Linguistics (ACL), 2001. link
8. A Decoder for Syntax-Based Statistical MT" (K. Yamada and K. Knight), Proc. of the Conference of the Association for Computational Linguistics (ACL), 2002. link
9. Syntax-based Language Models for Machine Translation, E. Charniak, K. Knight, and K. Yamada, Proc. MT Summit IX, 2003. link
10. Wang and Waibel, "Modeling with structures in statistical machine translation", Proceedings of COLING-ACL, 1998 link
11. Inducing Translation Templates for Example-Based Machine Translation, by Michael Carl. link
12. Reordering Constraints for Phrase-based Statistitical MT, by Richard Zens, Hermann Ney, Taro Watanabe, and Eiichiro Sumita, from Coling'04 link
13. Improving a Statistical MT System with Automatically Learned Rewrite Patterns, by Fei Xia and Michael McCord, COLING-2004. link
14. Dan Melamed (2004). Algorithms for Syntax-Aware Statistical Machine Translation PS PDF Proceedings of the Conference on Theoretical and Methodological Issues in Machine Translation (TMI'04), Baltimore, MD.

1. Decoding Algorithm in Statistical Machine Translation , Ye-Yi Wang and Alex Waibel Language Technology Institute School of Computer. Proceedings of the Thirty-Fifth Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics link
2. Search algorithms for statistical machine translation based on dynamic programming and pruning techniques, I. Garcia-Varea and F. Casacuberta, Proceedings of the MT Summit VIII Workshop, 2001, link
3. Germann, U., Jahr, M., Knight, K., Marcu, D., and Yamada, K. (2001). Fast decoding and optimal decoding for machine translation. In Proceedings of ACL 39. link
4. Vogel, Ney and Tillmann, "HMM-based word alignment in statistical translation", Proceedings of COLING 1996 link
5. Och and Ney, "A comparison of alignment models for statistical machine translation", Proceedings of COLING 2000 link
6. An Iterative, DP-based Search Algorithm for Statistical Machine Translation, Ismael Garccia-Varea, Francisco Casacuber, and Hermann Ney, ICSLP'98 link
7. A DP based Search Using Monotone Alignments in Statistical Translation (1997) C. Tillmann, S. Vogel, H. Ney, A. Zubiaga link
8. A DP based Search Algorithm for Statistical Machine Translation (1998) S. Niessen, S. Vogel, H. Ney, C. Tillmann link
9. Accelerated Dp Based Search For Statistical Translation (1997) C. Tillmann, S. Vogel, H. Ney, A. Zubiaga, H. Sawaf link
10. A Polynomial-Time Algorithm for Statistical Machine Translation Dekai Wu link

1. Knowledge Sources for Word-Level Translation Models, P. Koehn and K. Knight, link
2. Morpho-Syntactic Analysis for Reordering in Statistical Machine Translation (2001), Sonja Nieen, Hermann Ney link
3. Ismael Garcia Varea, Franz Josef Och, Hermann Ney, Francisco Casacuberta. "Refined Lexicon Models for Statistical Machine Translation using a Maximum Entropy Approach". In: "ACL 2001: Proc. of the 39th Annual Meeting of the Association for Computational Linguistics", pp. 204-211, Toulouse, France, July 2001. link<
4. Hearne, Mary and Way, Andy. 2003. Seeing the Wood for the Trees: Data-Oriented Translation. Proceedings of MT Summit IX. link

1. Improved Alignment Models for Statistical Machine Translation (1999), Franz Josef Och, Christoph Tillmann, Hermann Ney link
2. Loosely Tree-Based Alignment for Machine Translation, by Dan Gildea link (also see here for a JHU'03 presentation on the subject).

1. A Maximum Entropy/Minimum Divergence Translation Model (2000) George Foster, link

1. Class-based n-gram models of natural language by P. Brown, V. Della Pietra, P. deSouza, and J. Lai link
2. Language Model Adaptation for Statistical Machine Translation via Structured Query Models, by Bing Zhao, Matthias Eck and Stephan Vogel link

1. Statistical Multi-Source Translation, Franz Josef Och and Hermann Ney link
2. Discriminative Training and Maximum Entropy Models for Statistical Machine Translation, Franz Josef Och and Hermann Ney, Proc. 40th Annual Meeting of the ACL, Philadelphia, 2002 link
3. Minimum Error Rate Training in Statistical Machine Translation pp. 160-167 Franz Josef Och, ACL-2003 link
4. Franz Josef Och, Hermann Ney. What Can Machine Translation Learn from Speech Recognition? In: "Workshop: MT 2010 - Towards a Road Map for MT", pp. 26-31, Santiago de Compostela, Spain, September 2001. link
5. Models of Translational Equivalence among Words, I. Dan Melamed link
6. Towards a Unified Approach to Memory- and Statistical-Based Machine Translation, Daniel Marcu link
7. Machine Transliteration, (K. Knight and J. Graehl), Computational Linguistics, 24(4), 1998. link
8. Alshawi, H. and Douglas, S., ``Learning Dependency Transduction Models from Unannotated Examples,'' Phil Trans. of the Royal Society, Series A: Mathematical, Physical and Engineering Sciences, vol. 358, 2000, pp. 1357-1372. link, pdf link
9. "Machine Transliteration," (K. Knight and J. Graehl), Proc. of the Conference of the Association for Computational Linguistics (ACL), 1997.link
10. Confidence Estimation for Machine Translation, John Blatz, Erin Fitzgerald, George Foster, Simona Gandrabur, Cyril Goutte, Alex Kulesza, Alberto Sanchis and Nicola Ueffing, pp. 315-321, Coling 04, link
11. Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary, P. Duygulu, K. Barnard, J.F.G. de Freitas and D.A. Forsyth, 7th European Conference on Computer Vision (Best paper award winner). link

1. Examples and Prospects of Example Based MT E. Sumita, H. Iida, H. Kohyama (ATR). Proc. ACL 1991 link
2. Example Based MT in the Pangloss system RD Brown (CMU). Proc. ACL 1996 link

• The UW Turing Center investigates NLP, machine learning, web search, and semantic web.
• University of Washington, Computational Linguistics Discussions UWCL
• Discussion about MT that appeared on slash-dot. Click here for the thread.
• NAACL page.
• Bibliography for Statistical Alignment and Machine Translation
• From: Emily: I thought this book, from the perspective of human translation, might be of interest.
• ACL web
• ACL at upenn.
• Alshawi's non-IBM statistical methods
• Several people have asked where Jeff's EM tutorial is. You can find it: here
• Our sister reading group, the graphical/kernels reading group here