Preprocessing for English-to-Arabic Statistical Machine Translation

Zbib, Rabih; Badr, Ibrahim

doi:10.1075/nlp.9.06zbi

In:Challenges for Arabic Machine Translation
Edited by Abdelhadi Soudi, Ali Farghaly, Günter Neumann and Rabih Zbib
[Natural Language Processing 9] 2012
► pp. 95–108

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Preprocessing for English-to-Arabic Statistical Machine Translation

Rabih Zbib | Raytheon BBN Technologies, Cambridge MA, USA

Ibrahim Badr | Massachusetts Institute of Technology, Cambridge MA, USA

Published online: 1 August 2012

https://doi.org/10.1075/nlp.9.06zbi

Most research in Arabic Statistical Machine Translation (SMT) has focused on translating from Arabic into English and other languages. Translation to Arabic has drawn very little attention so far, despite being an important, as well as technically challenging task. This chapter describes the application of two preprocessing techniques to English-to-Arabic SMT: Morphological Segmentation and Syntactic Reordering. It shows how these techniques can be adapted to apply to translation into Arabic, providing significant improvements to a phrase-based system.

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Biadgligne, Yohanens & Kamel Smaïli

2021. Parallel Corpora Preparation for English-Amharic Machine Translation. In Advances in Computational Intelligence [Lecture Notes in Computer Science, 12861], ► pp. 443 ff.

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