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Advanced MT Seminar Spring 2010. Papers and Presentations. Kevin Gimpel.

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advanced mt seminar spring 2010

Advanced MT SeminarSpring 2010

Papers and Presentations

kevin gimpel
Kevin Gimpel
  • Translation Modeling:S. DeNeefe and K. Knight. Synchronous Tree Adjoining Machine Translation, EMNLP 2009.Link: Auli, Adam Lopez, Hieu Hoang, and Philipp Koehn.  A Systematic Analysis of Translation Model Search Spaces. WMT 2009.Link: Birch, Phil Blunsom and Miles Osborne. A Quantitative Analysis of Reordering Phenomena. WMT 2009.Link:
  • Alternative Training Criteria:Adam Pauls, John DeNero, and Dan Klein. Consensus Training for Consensus Decoding in Machine Translation. EMNLP 2009.Link: Li and Sanjeev Khudanpur. Forest Reranking for Machine Translation with the Perceptron Algorithm. To appear in the GALE book chapter on "MT from text", 2009.Link:
  • Presentation dates: prefer to not lead discussion on February 3rd or 10th.
greg hanneman
Greg Hanneman
  • "Decoding by Dynamic Chunking for Statistical Machine Translation"Yahyaei and MonzMT Summit 2009"Learning Accurate, Compact, and Interpretable Tree Annotation"Petrov, Barrett, Thibaux, and KleinACL 2006"Discriminative Reordering with Chinese Grammatical Relations Features"Chang, Tseng, Jurafsky, and ManningSSST 2009"Rule Filtering by Pattern for Efficient Hierarchical Translation"Iglesias, de Gispert, Banga, and ByrneEACL 2009"Improved Word Alignment with Statistics and Linguistic Heuristics"HermjakobEMNLP 2009
jaedy kim
Jaedy Kim
  • 1. Topic List     MT approach convergence     Data processing (pre- and post-)     Automatic transfer rule learning     Efficient decoding (for SMT, Syntax-based MT) 2. Paper Selection     Chunk-Level Reordering of Source Language Sentences with Automatically Learned Rules for Statistical Machine Translation.: Y. Zhang, R. Zens and H. Ney     Example-based Machine Translation Based on Syntactic Transfer with Statistical Models: Kenji Imamura, Hideo Okuma, Taro Watanabe and Eiichiro Sumita (ATR)     Pivot Language Approach for Phrase-Based Statistical Machine Translation: H. Wu and  H. Wang, (Toshiba, Beijing)     Information Retrieval as Statistical Translation : A. Berger and J. Lafferty     Generating Complex Morphology for Machine Translation: E. Minkov, K. Toutanova and H. Suzuki (MSR)
michael denkowski
Michael Denkowski
  • Variational Decoding for Statistical Machine Translation(Zhifei Li; Jason Eisner; Sanjeev Khudanpur) Minimum Error Rate Training and Minimum Bayes-Risk Decoding for Translation Hypergraphs and Lattices(Shankar Kumar; Wolfgang Macherey; Chris Dyer; Franz Och) Statistical Machine Translation Using Monolingually-Derived Paraphrases (Yuval Marton; Chris Callison-Burch; Philip Resnik) a maximum entropy model to build segmentation lattices for MT(Chris Dyer) of Human-in-the-loop Minimum Error Rate Training (Omar F. Zaidan; Chris Callison-Burch) Contribution of Linguistic Features to Automatic Machine Translation Evaluation(Enrique Amigó; Jesús Giménez; Julio Gonzalo; Felisa Verdejo)
nguyen bach
Nguyen Bach
  • + Sentence SimplificationHybrid Spoken Language Translation. Using Sentence Splitting Based on Syntax Structure. Satoshi Kamatani, Tetsuro Chino and Kazuo Sumita, MT-Summit 2009Sentence Compression Beyond Word Deletion, Trevor Cohn and Mirella Lapata, COLING 2008A Maximum Entropy-based Sentence Simplifier for Machine Translation, Finch et al., NLP-KE-2005Sentence splitting based on n-grams and select the best one by measuring sentence similarity, Doi and Sumita,  COLING 2004
  • + Word Sense DisambiguationWord sense disambiguation improves statistical machine translation. Yee Seng Chan, Hwee Tou Ng, and David Chiang, ACL-2007
  • I prefer to discuss these papers sometimes on the 3rd or 4th week of March.
qin gao
Qin Gao
  • Bodrumlu, T., K. Knight, and S. Ravi. “A new objective function for word alignment.” Proceedings of the Workshop on Integer Linear Programming for Natural Langauge Processing. 2009. 28–35. Link
  • Cherry, C., and D. Lin. “A probability model to improve word alignment.” Proceedings of the 41st Annual Meeting on Association for Computational Linguistics. 2003. 88–95. Link (Early paper)
  • Fossum, V., K. Knight, and S. Abney. “Using syntax to improve word alignment precision for syntax-based machine translation.” Proceedings of the Third Workshop on Statistical Machine Translation. 2008. 44–52. Link
  • Fraser, A., and D. Marcu. “Getting the structure right for word alignment: LEAF.” Proc. EMNLP-CoNLL. 2007. Link
  • Hermjakob, U. “Improved Word Alignment with Statistics and Linguistic Heuristics.”ACL 2009 Link
jon clark
Jon Clark
  • Cube Pruning as A* Search (LanguageWeaver):
  • Efficient Parsing for Transducer Grammars (DeNeero):
  • Unaligned Word Removal (Aachen):
  • Bayesian Tree to String Grammar Induction (Blunsom)
  • MERT and MBR on Hypergraphs (Dyer)
  • Jan 27: Hassan Al-Haj
  • Feb 3:
  • Feb 10:
  • Feb 17:
  • Feb 24:
  • Mar 3:
  • Mar 10:
  • Mar 17:
  • Mar 24:
  • Mar 31:
  • Apr 7:
  • Apr 14:
  • Apr 21:
  • Apr 28: