Extended Parallel Corpus for Amharic-English Machine Translation

This paper describes the acquisition, preprocessing, segmentation, and alignment of an AmharicEnglish parallel corpus. It will be useful for machine translation of an under-resourced language, Amharic. The corpus is larger than previously compiled corpora; it is released2 for research purposes. We trained neural machine translation and phrase-based statistical machine translation models using the corpus. In the automatic evaluation, neural machine translation models outperform phrase-based statistical machine translation models. 2012 ACM Subject Classification Computing methodologies → Machine translation

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