A systematic comparison of various statistical alignment models
Computational Linguistics
A program for aligning sentences in bilingual corpora
Computational Linguistics - Special issue on using large corpora: I
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
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical translation alignment with compositionality constraints
HLT-NAACL-PARALLEL '03 Proceedings of the HLT-NAACL 2003 Workshop on Building and using parallel texts: data driven machine translation and beyond - Volume 3
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
Using normalized alignment scores to detect incorrectly aligned segments
Proceedings of the 2nd international workshop on Patent information retrieval
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In statistical machine translation, large numbers of parallel sentences are required to train the model parameters. However, plenty of the bilingual language resources available on web are aligned only at the document level. To exploit this data, we have to extract the bilingual sentences from these documents. The common method is to break the documents into segments using predefined anchor words, then these segments are aligned. This approach is not error free, incorrect alignments may decrease the translation quality. We present an alternative approach to extract the parallel sentences by partitioning a bilingual document into two pairs. This process is performed recursively until all the sub-pairs are short enough. In experiments on the Chinese-English FBIS data, our method was capable of producing translation results comparable to those of a state-of-the-art sentence aligner. Using a combination of the two approaches leads to better translation performance.