USAAR: An Operation Sequential Model for Automatic Statistical Post-Editing

Abstract

This paper presents an automatic post editing (APE) method to improve the translation quality produced by an English-German (EN-DE) statistical machine translation (SMT) system. Our system is based on Operation Sequential Model (OSM) combined with phrased based statistical MT (PB-SMT) system. The system is trained on monolingual settings between MT outputs (TLMT ) produced by a black-box MT system and their corresponding post-edited version (TLPE). Our system achieves considerable improvement over TLMT on a held-out development set. The reported system achieves 64.10 BLEU (1.99 absolute points and 3.2% relative improvement in BLEU over raw MT output) and 24.14 TER and a TER score of 24.14 (0.66 absolute points and 0.25% relative improvement in TER over raw MT output) in the official test set.