The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Arabic preprocessing schemes for statistical machine translation
Open accessAbstract
In this paper, we study the effect of different word-level preprocessing decisions for Arabic on SMT quality. Our results show that given large amounts of training data, splitting off only proclitics performs best. However, for small amounts of training data, it is best to apply English-like to-kenization using part-of-speech tags, and sophisticated morphological analysis and disambiguation. Moreover, choosing the appropriate preprocessing produces a significant increase in BLEU score if there is a change in genre between training and test data.
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BLEU: a method for automatic evaluation of machine translation
Papineni, K., Roukos, S., Ward, T., & Zhu, W.-J. (2001) · Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02 · doi:10.3115/1073083.1073135 · Cited by 21,344
Cited by
A Simple, Fast, and Effective Reparameterization of IBM Model 2
Dyer, C., Chahuneau, V., & Smith, N. A. (2018) · doi:10.1184/r1/6472985 · Cited by 767
Darwish, K., & Magdy, W. (2014) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000031 · Cited by 102
Integrating an Unsupervised Transliteration Model into Statistical Machine Translation
Durrani, N., Sajjad, H., Hoang, H., & Koehn, P. (2014) · Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics, volume 2: Short Papers · doi:10.3115/v1/e14-4029 · Cited by 89
Metadata
- Authors
- Habash, N., & Sadat, F.
- Venue
- Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX - NAACL '06
- Published
- 2006
- Pages
- 49-52
- OpenAlex
- W2135161317
- Cited by
- 253
- References
- 1
- FWCI
- 13.45
- Type
- conference paper
- Language
- en
- Open access
- gold
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