SOTAVerified

Faster and Lighter Phrase-based Machine Translation Baseline

2016-12-01WS 2016Unverified0· sign in to hype

Liling Tan

Unverified — Be the first to reproduce this paper.

Reproduce

Abstract

This paper describes the SENSE machine translation system participation in the Third Workshop for Asian Translation (WAT2016). We share our best practices to build a fast and light phrase-based machine translation (PBMT) models that have comparable results to the baseline systems provided by the organizers. As Neural Machine Translation (NMT) overtakes PBMT as the state-of-the-art, deep learning and new MT practitioners might not be familiar with the PBMT paradigm and we hope that this paper will help them build a PBMT baseline system quickly and easily.

Tasks

Reproductions