Robust parfda Statistical Machine Translation Results

EMNLP 2018 Ergun Bi{\c{c}}ici

We build parallel feature decay algorithms (parfda) Moses statistical machine translation (SMT) models for language pairs in the translation task. parfda obtains results close to the top constrained phrase-based SMT with an average of 2.252 BLEU points difference on WMT 2017 datasets using significantly less computation for building SMT systems than that would be spent using all available corpora... (read more)

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