Joshua 4.0: packing, PRO, and paraphrases

Authors:
Juri Ganitkevitch;Yuan Cao;Jonathan Weese;Matt Post;Chris Callison-Burch
Affiliations:
Johns Hopkins University;Johns Hopkins University;Johns Hopkins University;Johns Hopkins University;Johns Hopkins University
Venue:
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
Year:
2012

Citing 16
Cited 2

Minimum error rate training in statistical machine translation

ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Optimization, maxent models, and conditional estimation without magic

NAACL-Tutorials '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Tutorials - Volume 5
Paraphrasing with bilingual parallel corpora

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Hierarchical Phrase-Based Translation

Computational Linguistics
Domain adaptation for statistical classifiers

Journal of Artificial Intelligence Research
Joshua: an open source toolkit for parsing-based machine translation

StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
How many bits are needed to store probabilities for phrase-based translation?

StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Two monolingual parses are better than one (synchronous parse)

HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Joshua 2.0: a toolkit for parsing-based machine translation with syntax, semirings, discriminative training and other goodies

WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
Unsupervised discriminative language model training for machine translation using simulated confusion sets

COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Faster and smaller N-gram language models

HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Learning to Rank for Information Retrieval and Natural Language Processing

Learning to Rank for Information Retrieval and Natural Language Processing
KenLM: faster and smaller language model queries

WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Joshua 3.0: syntax-based machine translation with the Thrax grammar extractor

WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
Learning sentential paraphrases from bilingual parallel corpora for text-to-text generation

EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Tuning as ranking

EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing

Monolingual distributional similarity for text-to-text generation

SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
Findings of the 2012 workshop on statistical machine translation

WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present Joshua 4.0, the newest version of our open-source decoder for parsing-based statistical machine translation. The main contributions in this release are the introduction of a compact grammar representation based on packed tries, and the integration of our implementation of pairwise ranking optimization, J-PRO. We further present the extension of the Thrax SCFG grammar extractor to pivot-based extraction of syntactically informed sentential paraphrases.