Indexed metadata

Is Neural Machine Translation the New State of the Art?

Sheila Castilho, Joss Moorkens, Federico Gaspari, Iacer Calixto, John Tinsley, Andy Way

Source record

Source: Crossref

Published: Jun 1, 2017

DOI: 10.1515/pralin-2017-0013

Open original source ↗

Source abstract

Abstract This paper discusses neural machine translation (NMT), a new paradigm in the MT field, comparing the quality of NMT systems with statistical MT by describing three studies using automatic and human evaluation methods. Automatic evaluation results presented for NMT are very promising, however human evaluations show mixed results. We report increases in fluency but inconsistent results for adequacy and post-editing effort. NMT undoubtedly represents a step forward for the MT field, but one that the community should be careful not to oversell.

Evidence graph

No public relationships recorded yet.

Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.

Is Neural Machine Translation the New State of the Art? — Mathematical Frontier Network