Automatic Post-Editing of Machine Translation: A Neural Programmer-Interpreter Approach

Code

• github.com/trangvu/ape-npi
  tf★ 4

Abstract

Automated Post-Editing (PE) is the task of automatically correct common and repetitive errors found in machine translation (MT) output. In this paper, we present a neural programmer-interpreter approach to this task, resembling the way that human perform post-editing using discrete edit operations, wich we refer to as programs. Our model outperforms previous neural models for inducing PE programs on the WMT17 APE task for German-English up to +1 BLEU score and -0.7 TER scores.

Tasks

Reproductions