most citedIs Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions

150 citations · 167 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2024

PyMarian: Fast Neural Machine Translation and Evaluation in Python

Thamme Gowda, Roman Grundkiewicz, Elijah Rippeth +2

The deep learning language of choice these days is Python; measured by factors such as available libraries and technical support, it is hard to beat. At the same time, software wri…

cs.CL2023

SOTASTREAM: A Streaming Approach to Machine Translation Training

Matt Post, Thamme Gowda, Roman Grundkiewicz +3

Many machine translation toolkits make use of a data preparation step wherein raw data is transformed into a tensor format that can be used directly by the trainer. This preparatio…

cs.CL201715 cited

An Exploration of Neural Sequence-to-Sequence Architectures for Automatic Post-Editing

Marcin Junczys-Dowmunt, Roman Grundkiewicz

In this work, we explore multiple neural architectures adapted for the task of automatic post-editing of machine translation output. We focus on neural end-to-end models that combi…

cs.CL2016150 cited

Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions

Marcin Junczys-Dowmunt, Tomasz Dwojak, Hieu Hoang

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 direc…

cs.CL20162 cited

Fast, Scalable Phrase-Based SMT Decoding

Hieu Hoang, Nikolay Bogoychev, Lane Schwartz +1

The utilization of statistical machine translation (SMT) has grown enormously over the last decade, many using open-source software developed by the NLP community. As commercial us…