English

Multi-Source Neural Translation

Computation and Language 2016-01-06 v1

Abstract

We build a multi-source machine translation model and train it to maximize the probability of a target English string given French and German sources. Using the neural encoder-decoder framework, we explore several combination methods and report up to +4.8 Bleu increases on top of a very strong attention-based neural translation model.

Keywords

Cite

@article{arxiv.1601.00710,
  title  = {Multi-Source Neural Translation},
  author = {Barret Zoph and Kevin Knight},
  journal= {arXiv preprint arXiv:1601.00710},
  year   = {2016}
}

Comments

5 pages, 6 figures

R2 v1 2026-06-22T12:22:55.964Z