Abstract
We present a new method for aligning sentences with their translations in a parallel bilingual corpus. Previous approaches have generally been based either on sentence length or word correspondences. Sentence-length-based methods are relatively fast and fairly accurate. Word-correspondence-based methods are generally more accurate but much slower, and usually depend on cognates or a bilingual lexicon. Our method adapts and combines these approaches, achieving high accuracy at a modest computational cost, and requiring no knowledge of the languages or the corpus beyond division into words and sentences.
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References
Kay, M., Röscheisen, M.: Text-Translation Alignment. Technical Report, Xerox Palo Alto Research Center (1988)
Kay, M., Röscheisen, M.: Text-Translation Alignment. Computational Linguistics 19(1) (1993) 121–142
Brown, P.F., Lai, J.C., Mercer, R.L.: Aligning Sentences in Parallel Corpora. In Proceedings of the 29th Annual Meeting of the Association for Computational Linguistics, Berkeley, California (1991) 169–176
Gale, W.A., Church, K.W.: A program for Aligning Sentences in Bilingual Corpora. In Proceedings of the 29th Annual Meeting of the Association for Computational Linguistics, Berkeley, California (1991) 177–184
Gale, W.A., Church, K.W.: A Program for Aligning Sentences in Bilingual Corpora. Computational Linguistics 19(1) (1993) 75–102
Chen, S.F.: 1993. Aligning Sentences in Bilingual Corpora Using Lexical Information. In Proceedings of the 31st Annual Meeting of the Association for Computational Linguistics, Columbus, Ohio (1993) 9–16
Wu, D.: Aligning a Parallel English-Chinese Corpus Statistically with Lexical Criteria. In Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics, Las Cruces, New Mexico (1994) 80–87
Melamed, I.D.: A Geometric Approach to Mapping Bitext Correspondence. IRCS Technical Report 96-22, University of Pennsylvania (1996)
Melamed, I.D.: A Portable Algorithm for Mapping Bitext Correspondence. In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics, Madrid, Spain (1997) 305–312
Simard, M., Plamondon, P.: Bilingual Sentence Alignment: Balancing Robustness and Accuracy. Machine Translation 13(1) (1998) 59–80
Brown, PR, Delia Pietra, S. A., Della Pietra, V. J., Mercer, R.L.: The Mathematics of Statistical Machine Translation: Parameter Estimation. Computational Linguistics 19(2) (1993) 263–311
Rabiner, L. R.: A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proceedings of the IEEE 77(2) (1989) 257–286
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© 2002 Springer-Verlag Berlin Heidelberg
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Moore, R.C. (2002). Fast and Accurate Sentence Alignment of Bilingual Corpora. In: Richardson, S.D. (eds) Machine Translation: From Research to Real Users. AMTA 2002. Lecture Notes in Computer Science(), vol 2499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45820-4_14
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DOI: https://doi.org/10.1007/3-540-45820-4_14
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