A Corpus Level MIRA Tuning Strategy for Machine Translation

MIRA based tuning methods have been widely used in statistical machine translation (SMT) system with a large number of features. Since the corpus-level BLEU is not decomposable, these MIRA approaches usually define a variety of heuristic-driven sentencelevel BLEUs in their model losses. Instead, we present a new MIRA method, which employs an exact corpus-level BLEU to compute the model loss. Our method is simpler in implementation. Experiments on Chinese-toEnglish translation show its effectiveness over two state-of-the-art MIRA implementations.

[1]  Philipp Koehn,et al.  Moses: Open Source Toolkit for Statistical Machine Translation , 2007, ACL.

[2]  Salim Roukos,et al.  Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.

[3]  Philipp Koehn,et al.  SampleRank Training for Phrase-Based Machine Translation , 2011, WMT@EMNLP.

[4]  George F. Foster,et al.  Batch Tuning Strategies for Statistical Machine Translation , 2012, NAACL.

[5]  Ben Taskar,et al.  An End-to-End Discriminative Approach to Machine Translation , 2006, ACL.

[6]  Philipp Koehn,et al.  Monte Carlo inference and maximization for phrase-based translation , 2009, CoNLL.

[7]  Chin-Yew Lin,et al.  ORANGE: a Method for Evaluating Automatic Evaluation Metrics for Machine Translation , 2004, COLING.

[8]  Franz Josef Och,et al.  Minimum Error Rate Training in Statistical Machine Translation , 2003, ACL.

[9]  Philip Resnik,et al.  Online Large-Margin Training of Syntactic and Structural Translation Features , 2008, EMNLP.

[10]  Kevin Knight,et al.  11,001 New Features for Statistical Machine Translation , 2009, NAACL.

[11]  David Chiang,et al.  Hierarchical Phrase-Based Translation , 2007, CL.

[12]  Vladimir Eidelman,et al.  Optimization Strategies for Online Large-Margin Learning in Machine Translation , 2012, WMT@NAACL-HLT.

[13]  Koby Crammer,et al.  Online Passive-Aggressive Algorithms , 2003, J. Mach. Learn. Res..

[14]  J. Platt.  Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines , 1998 .

[15]  David Chiang,et al.  Hope and Fear for Discriminative Training of Statistical Translation Models , 2012, J. Mach. Learn. Res..

[16]  Taro Watanabe,et al.  Online Large-Margin Training for Statistical Machine Translation , 2007, EMNLP.

[17]  Hermann Ney,et al.  Discriminative Training and Maximum Entropy Models for Statistical Machine Translation , 2002, ACL.

[18]  Taro Watanabe,et al.  Optimized Online Rank Learning for Machine Translation , 2012, NAACL.

[19]  Thomas Hofmann,et al.  Support vector machine learning for interdependent and structured output spaces , 2004, ICML.