Character-Aware Decoder for Translation into Morphologically Rich Languages

WS 2019 Adithya RenduchintalaPamela ShapiroKevin DuhPhilipp Koehn

Neural machine translation (NMT) systems operate primarily on words (or sub-words), ignoring lower-level patterns of morphology. We present a character-aware decoder designed to capture such patterns when translating into morphologically rich languages... (read more)

PDF Abstract WS 2019 PDF WS 2019 Abstract


No code implementations yet. Submit your code now

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper