A statistical approach to machine translation
Computational Linguistics
Bilingual Sentence Alignment: Balancing Robustness and Accuracy
Machine Translation
Fast and Accurate Sentence Alignment of Bilingual Corpora
AMTA '02 Proceedings of the 5th Conference of the Association for Machine Translation in the Americas on Machine Translation: From Research to Real Users
A systematic comparison of various statistical alignment models
Computational Linguistics
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
Methods and practical issues in evaluating alignment techniques
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Aligning sentences in parallel corpora
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
A program for aligning sentences in bilingual corpora
ACL '91 Proceedings of the 29th annual meeting on Association for Computational Linguistics
Char_align: a program for aligning parallel texts at the character level
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Aligning sentences in bilingual corpora using lexical information
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Aligning a parallel English-Chinese corpus statistically with lexical criteria
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Improved sentence alignment on parallel web pages using a stochastic tree alignment model
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Transferring structural markup across translations using multilingual alignment and projection
Proceedings of the 10th annual joint conference on Digital libraries
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Several algorithms are available for sentence alignment, but there is a lack of systematic evaluation and comparison of these algorithms under different conditions. In most cases, the factors which can significantly affect the performance of a sentence alignment algorithm have not been considered while evaluating. We have used a method for evaluation that can give a better estimate about a sentence alignment algorithm's performance, so that the best one can be selected. We have compared four approaches using this method. These have mostly been tried on European language pairs. We have evaluated manually-checked and validated English-Hindi aligned parallel corpora under different conditions. We also suggest some guidelines on actual alignment.