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QCRI Machine Translation Systems for IWSLT 16

arXiv · · Notable

NLP Arabic AI Research Translation

Summary

This paper describes QCRI's machine translation systems for the IWSLT 2016 evaluation campaign, focusing on Arabic-English and English-Arabic tracks. They built both Phrase-based and Neural machine translation models. A Neural MT system, trained by stacking data from different genres through fine-tuning, and applying ensemble over 8 models, outperformed a strong phrase-based system by 2 BLEU points in the Arabic->English direction. Why it matters: The research highlights the early promise of neural machine translation for Arabic language pairs, demonstrating its potential to surpass traditional methods.

Keywords

machine translation · Arabic-English · NMT · phrase-based · QCRI

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