Inducing Probabilistic Grammars by Bayesian Model Merging
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
A minimum description length approach to grammar inference
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing
A systematic comparison of various statistical alignment models
Computational Linguistics
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora
Computational Linguistics
HMM-based word alignment in statistical translation
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Programming languages and their compilers: Preliminary notes
Programming languages and their compilers: Preliminary notes
A hierarchical phrase-based model for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Scalable inference and training of context-rich syntactic translation models
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Hierarchical Phrase-Based Translation
Computational Linguistics
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Inversion transduction grammar for joint phrasal translation modeling
SSST '07 Proceedings of the NAACL-HLT 2007/AMTA Workshop on Syntax and Structure in Statistical Translation
SSST '09 Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation
A Gibbs sampler for phrasal synchronous grammar induction
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Better word alignments with supervised ITG models
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Learning stochastic bracketing inversion transduction grammars with a cubic time biparsing algorithm
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Joint parsing and alignment with weakly synchronized grammars
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Inducing synchronous grammars with slice sampling
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Word alignment with Stochastic Bracketing Linear Inversion Transduction Grammar
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Hierarchical search for word alignment
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
An unsupervised model for joint phrase alignment and extraction
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Unsupervised learning of event AND-OR grammar and semantics from video
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Machine translation without words through substring alignment
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Hi-index | 0.00 |
We argue that for purely incremental unsupervised learning of phrasal inversion transduction grammars, a minimum description length driven, iterative top-down rule segmentation approach that is the polar opposite of Saers, Addanki, and Wu's previous 2012 bottom-up iterative rule chunking model yields significantly better translation accuracy and grammar parsimony. We still aim for unsupervised bilingual grammar induction such that training and testing are optimized upon the same exact underlying model--a basic principle of machine learning and statistical prediction that has become unduly ignored in statistical machine translation models of late, where most decoders are badly mismatched to the training assumptions. Our novel approach learns phrasal translations by recursively subsegmenting the training corpus, as opposed to our previous model--where we start with a token-based transduction grammar and iteratively build larger chunks. Moreover, the rule segmentation decisions in our approach are driven by a minimum description length objective, whereas the rule chunking decisions were driven by a maximum likelihood objective. We demonstrate empirically how this trades off maximum likelihood against model size, aiming for a more parsimonious grammar that escapes the perfect overfitting to the training data that we start out with, and gradually generalizes to previously unseen sentence translations so long as the model shrinks enough to warrant a looser fit to the training data. Experimental results show that our approach produces a significantly smaller and better model than the chunking-based approach.