research
∙
08/14/2023
SOTASTREAM: A Streaming Approach to Machine Translation Training
Many machine translation toolkits make use of a data preparation step wh...
share
research
∙
04/25/2023
Escaping the sentence-level paradigm in machine translation
It is well-known that document context is vital for resolving a range of...
research
∙
09/17/2021
The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task
This paper presents the JHU-Microsoft joint submission for WMT 2021 qual...
research
∙
09/12/2021
Levenshtein Training for Word-level Quality Estimation
We propose a novel scheme to use the Levenshtein Transformer to perform ...
research
∙
07/22/2021
To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation
Automatic metrics are commonly used as the exclusive tool for declaring ...
research
∙
04/21/2021
On User Interfaces for Large-Scale Document-Level Human Evaluation of Machine Translation Outputs
Recent studies emphasize the need of document context in human evaluatio...
research
∙
04/14/2021
The Curious Case of Hallucinations in Neural Machine Translation
In this work, we study hallucinations in Neural Machine Translation (NMT...
research
∙
07/14/2019
Microsoft Translator at WMT 2019: Towards Large-Scale Document-Level Neural Machine Translation
This paper describes the Microsoft Translator submissions to the WMT19 n...
research
∙
09/01/2018
Dual Conditional Cross-Entropy Filtering of Noisy Parallel Corpora
In this work we introduce dual conditional cross-entropy filtering for n...
research
∙
09/01/2018
Microsoft's Submission to the WMT2018 News Translation Task: How I Learned to Stop Worrying and Love the Data
This paper describes the Microsoft submission to the WMT2018 news transl...
research
∙
09/01/2018
MS-UEdin Submission to the WMT2018 APE Shared Task: Dual-Source Transformer for Automatic Post-Editing
This paper describes the Microsoft and University of Edinburgh submissio...
research
∙
08/27/2018
Accelerating Asynchronous Stochastic Gradient Descent for Neural Machine Translation
In order to extract the best possible performance from asynchronous stoc...
research
∙
05/30/2018
Marian: Cost-effective High-Quality Neural Machine Translation in C++
This paper describes the submissions of the "Marian" team to the WNMT 20...
research
∙
04/16/2018
Near Human-Level Performance in Grammatical Error Correction with Hybrid Machine Translation
We combine two of the most popular approaches to automated Grammatical E...
research
∙
04/16/2018
Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task
Previously, neural methods in grammatical error correction (GEC) did not...
research
∙
04/01/2018
Marian: Fast Neural Machine Translation in C++
We present Marian, an efficient and self-contained Neural Machine Transl...
research
∙
03/15/2018
Achieving Human Parity on Automatic Chinese to English News Translation
Machine translation has made rapid advances in recent years. Millions of...
research
∙
06/13/2017
An Exploration of Neural Sequence-to-Sequence Architectures for Automatic Post-Editing
In this work, we explore multiple neural architectures adapted for the t...
research
∙
03/13/2017
Nematus: a Toolkit for Neural Machine Translation
We present Nematus, a toolkit for Neural Machine Translation. The toolki...
research
∙
02/03/2017
Predicting Target Language CCG Supertags Improves Neural Machine Translation
Neural machine translation (NMT) models are able to partially learn synt...
research
∙
10/13/2016
Fast, Scalable Phrase-Based SMT Decoding
The utilization of statistical machine translation (SMT) has grown enorm...
research
∙
10/04/2016
Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions
In this paper we provide the largest published comparison of translation...
research
∙
07/05/2016
Target-Side Context for Discriminative Models in Statistical Machine Translation
Discriminative translation models utilizing source context have been sho...
research
∙
05/20/2016
Phrase-based Machine Translation is State-of-the-Art for Automatic Grammatical Error Correction
In this work, we study parameter tuning towards the M^2 metric, the stan...
research
∙
05/16/2016
The AMU-UEDIN Submission to the WMT16 News Translation Task: Attention-based NMT Models as Feature Functions in Phrase-based SMT
This paper describes the AMU-UEDIN submissions to the WMT 2016 shared ta...
research
∙
05/16/2016
