11-731 Machine Translation: Additional Readings - Spring 2009

Lecture 1: Language Divergences, MT Challenges

• ALPAC Reprot. MT News International 14 (June 1996), 9-12.

Lecture 3: Components of an SMT System

• A Statistical Approach to Machine Translation. Peter F. Brown et al. Computational Linguistics, Vol. 16, No. 2. (June 1990), pp. 79-85.

Lecture 5: Word Alignment Models

• A Systematic Comparison of Various Statistical Alignment Models. Franz Josef Och and Hermann Ney. Computational Linguistics, (2003), vol. 29, no.1, pp. 19-51
• The Mathematics of Statistical Machine Translation. Peter F. Brown, Vincent J. Della Pietra, Stephen A. Della Pietra, Robert L. Mercer. Computational Linguistics, (1993), vol. 19, no. 2
• HMM-based Word Alignment in Statistical Translation. Stephan Vogel, Hermann Ney, Christoph Tillmann. COLING, The 16th Int. Conf. on Computational Linguistics, Copenhagen, Denmark, August 1996, pp. 836-841.

Lecture 6: Word Alignment Models (Cont.)

• A Statistical MT Tutorial Workbook. Keving Knight. Unpulished, August 1999

Lecture 7: Phrase Alignment

• Statistical phrase-based translation. Philipp Koehn, Franz Josef Och, and Daniel Marcu. In Proc. of the Annual Meeting of the Association for Computational Linguistics, 2003.

Lecture 8

• Stochastic Inversion Transduction Grammars and Bilingual Parsing of Parallel Corpora. Dekai Wu. Computational Linguistics (1997), Vol. 23, Num. 3, Pages 377-403.

Lecture 9: Syntax-based Word Alignment

• A hierarchical phrase-based model for statistical machine translation. David Chiang. ACL-2005: 43rd Annual meeting of the Association for Computational Linguistics, University of Michigan, Ann Arbor, 25-30 June 2005; pp. 263-270.
• Syntax augmented machine translation via chart parsing. Andreas Zollmann and Ashish Venugopal. HLT-NAACL 2006: Proceedings of the Workshop on Statistical Machine Translation, New York, NY, USA, June 2006; pp. 138-141.
• Syntax-driven learning of sub-sentential translation equivalents and translation rules from parsed parallel corpora. Alon Lavie, Alok Parlikar, and Vamshi Ambati. Second ACL Workshop on Syntax and Structure in Statistical Translation (ACL-08 SSST-2), Proceedings, 20 June 2008, Columbus, Ohio, USA; pp.87-95.
• What's in a translation rule?. Michel Galley, Mark Hopkins, Kevin Knight and Daniel Marcu. HLT-NAACL 2004: Human Language Technology conference and North American Chapter of the Association for Computational Linguistics annual meeting, May 2-7, 2004, The Park Plaza Hotel, Boston, USA; pp.273-280.

Lecture 11: Automatic MT Evaluation

• BLEU: a Method for Automatic Evaluation of Machine Translation. Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. in Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL-2002), Philadelphia, PA, July 2002.
• METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments. Satanjeev Banerjee, and Alon Lavie. In Proceedings of Workshop on Intrinsic and Extrinsic Evaluation Measures for MT and/or Summarization at the 43th Annual Meeting of the Association of Computational Linguistics (ACL-2005), Ann Arbor, Michigan, June 2005. Pages 65-72.

Lecture 13: Phrase-based Decoding

• SMT Decoder Dissected: Word Reordering. Stephan Vogel. International Conference on Natural Language Processing and Knowledge Engineering (NLP-KE'03), Beijing, China. October 2003.

Lecture 15: Phrase-based Decoding (Cont.) and Chart-based Decoding

• Improvements in Dynamic Programming Beam Search for Phrase-based Statistical Machine Translation. Richard Zens and Hermann Ney. In Proceedings of the International Workshop on Spoken Language Translation (IWSLT), Honolulu, HI, October 2008.

Lecture 16: Minimum Error Rate Training

• Minimum Error Rate Training in Statistical Machine Translation. Franz Josef Och. 41st Annual meeting of the Association for Computational Linguistics, 2003.
• Automatic Evaluation Measures for Statistical Machine Translation System Optimization. A. Mauser, S. Hasan, and H. Ney. In International Conference on Language Resources and Evaluation (LREC), Marrakech, Morocco, May 2008.

Lecture 17: Languge Models

• An Empirical Study of Smoothing Techniques for Language Modeling. S. F. Chen and J. Goodman. TR-10-98, Computer Science Group, Harvard Univ., 1998.