A statistical approach to machine translation
Computational Linguistics
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Adaptive Parallel Sentences Mining from Web Bilingual News Collection
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Automatic construction of English/Chinese parallel corpora
Journal of the American Society for Information Science and Technology
Computational Linguistics - Special issue on web as corpus
A program for aligning sentences in bilingual corpora
Computational Linguistics - Special issue on using large corpora: I
An IR approach for translating new words from nonparallel, comparable texts
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Identifying word translations in non-parallel texts
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
A bootstrapping method for extracting bilingual text pairs
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Discriminative training and maximum entropy models for statistical machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Word sense acquisition from bilingual comparable corpora
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Reliable measures for aligning Japanese-English news articles and sentences
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
Improving Machine Translation Performance by Exploiting Non-Parallel Corpora
Computational Linguistics
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Named entity transliteration with comparable corpora
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Extracting parallel sub-sentential fragments from non-parallel corpora
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Mining key phrase translations from web corpora
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Finding translations for low-frequency words in comparable corpora
Machine Translation
Statistical machine translation
ACM Computing Surveys (CSUR)
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
On the use of comparable corpora to improve SMT performance
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Language and translation model adaptation using comparable corpora
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Further meta-evaluation of machine translation
StatMT '08 Proceedings of the Third Workshop on Statistical Machine Translation
Fluency, adequacy, or HTER?: exploring different human judgments with a tunable MT metric
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Extracting lay paraphrases of specialized expressions from monolingual comparable medical corpora
BUCC '09 Proceedings of the 2nd Workshop on Building and Using Comparable Corpora: from Parallel to Non-parallel Corpora
Mining name translations from comparable corpora by creating bilingual information networks
BUCC '09 Proceedings of the 2nd Workshop on Building and Using Comparable Corpora: from Parallel to Non-parallel Corpora
Exploiting comparable corpora with TER and TERp
BUCC '09 Proceedings of the 2nd Workshop on Building and Using Comparable Corpora: from Parallel to Non-parallel Corpora
Can crowds build parallel corpora for machine translation systems?
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
Using Mechanical Turk to build machine translation evaluation sets
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
Large scale parallel document mining for machine translation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Automatic acquisition of chinese–english parallel corpus from the web
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
ACCURAT toolkit for multi-level alignment and information extraction from comparable corpora
ACL '12 Proceedings of the ACL 2012 System Demonstrations
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
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A parallel corpus is an essential resource for statistical machine translation (SMT) but is often not available in the required amounts for all domains and languages. An approach is presented here which aims at producing parallel corpora from available comparable corpora. An SMT system is used to translate the source-language part of a comparable corpus and the translations are used as queries to conduct information retrieval from the target-language side of the comparable corpus. Simple filters are then used to score the SMT output and the IR-returned sentence with the filter score defining the degree of similarity between the two. Using SMT system output gives the benefit of trying to correct one of the common errors by sentence tail removal. The approach was applied to Arabic---English and French---English systems using comparable news corpora and considerable improvements were achieved in the BLEU score. We show that our approach is independent of the quality of the SMT system used to make the queries, strengthening the claim of applicability of the approach for languages and domains with limited parallel corpora available to start with. We compare our approach with one of the earlier approaches and show that our approach is easier to implement and gives equally good improvements.