Paper Info
Title
Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions.
Abstract
In this paper we provide the largest published comparison of translation quality for phrase-based SMT and neural machine translation across 30 translation directions. For ten directions we also include hierarchical phrase-based MT. Experiments are performed for the recently published United Nations Parallel Corpus v1.0 and its large six-way sentence-aligned subcorpus. In the second part of the paper we investigate aspects of translation speed, introducing AmuNMT, our efficient neural machine translation decoder. We demonstrate that current neural machine translation could already be used for in-production systems when comparing words-per-second ratios.
Year
Venue
Field
2016
arXiv: Computation and Language
Rule-based machine translation,Example-based machine translation,Computer science,Evaluation of machine translation,Machine translation,Synchronous context-free grammar,Machine translation software usability,Natural language processing,Transfer-based machine translation,Artificial intelligence,Computer-assisted translation,Machine learning
DocType
Volume
Citations 
Journal
abs/1610.01108
36
PageRank 
References 
Authors
1.54
14
3
Name
Order
Citations
PageRank
Marcin Junczys-Dowmunt131224.24
Tomasz Dwojak2361.54
Hieu Hoang3151868.35