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This article describes a machine translation system based on an automatic post-editing strategy: initially translate the input text into the target-language using a rule-based MT system, then automatically post-edit the …...

We propose to use a statistical phrase- based machine translation system in a post-editing task: the system takes as in- put raw machine translation output (from a commercial rule-based MT …...

This paper describes the two systems sub- mitted by LIMSI to the WMT’15 Shared Task on Automatic Post-Editing. The first one relies on a reformulation of the APE task as …...

AbstractIn this paper we combine two strands of machine translation (MT) research: automatic post-editing (APE) and multi-engine (system combination) MT. APE systems learn a target-language-side second stage MT system from …...

This work presents a novel approach to Automatic Post-Editing (APE) and Word- Level Quality Estimation (QE) using en- sembles of specialized Neural Machine Translation (NMT) systems. Word-level features that have …...

This paper presents the results of the WMT17 shared tasks, which included three machine translation (MT) tasks (news, biomedical, and multimodal), two evaluation tasks (metrics and run-time es- timation of …...

This paper presents the LIG-CRIStAL submission to the shared Automatic Post- Editing task of WMT 2017. We propose two neural post-editing models: a mono- source model with a task-specific atten- …...

Previous phrase-based approaches to Au- tomatic Post-editing (APE) have shown that the dependency of MT errors from the source sentence can be exploited by jointly learning from source and target …...

Automatic post-editing (APE) is a challenging task on WMT evaluation campaign. We find that only a small number of edit operations are required for most machine translation outputs, through analysis …...

AbstractTranslation quality estimation is a task of growing importance in NLP, due to its potential to reduce post-editing human effort in disruptive ways. However, this potential is currently limited by …...

This work describes the AMU-UEdin sub- mission to the WMT 2017 shared task on Automatic Post-Editing. We explore mul- tiple neural architectures adapted for the task of automatic post-editing of …...

We investigate different strategies for combining quality estimation (QE) and automatic post- editing (APE) to improve the output of machine translation (MT) systems. The joint contribu- tion of the two …...

Training models for the automatic correction of machine-translated text usually relies on data consisting of (source, MT, human post- edit) triplets providing, for each source sentence, examples of translation errors …...

AbstractAutomatic post-editing (APE) seeks to automatically refine the output of a black-box machine translation (MT) system through human post-edits. APE systems are usually trained by complementing human post-edited data with …...

Two of the more predominant technologies that professional translators have at their disposal for improving productivity are machine translation (MT) and computer- aided translation (CAT) tools based on translation memories …...

AbstractAutomatic post-editing (APE), which aims to correct errors in the output of machine translation systems in a post-processing step, is an important task in natural language processing. While recent work …...

AbstractWe introduce a machine translation dataset for three pairs of languages in the legal domain with post-edited high-quality neural machine translation and independent human references. The data was collected as …...

AbstractThis paper introduces the first corpus for Automatic Post-Editing of English and a low-resource language, Brazilian Portuguese. The source English texts were extracted from the WebNLG corpus and automatically translated …...

AbstractWith the advent of neural machine translation, there has been a marked shift towards leveraging and consuming the machine translation results. However, the gap between machine translation systems and human …...

AbstractIn this paper, we describe the Bering Lab’s submission to the WMT 2020 Shared Task on Automatic Post-Editing (APE). First, we propose a cross-lingual Transformer architecture that takes a concatenation …...

AbstractWe present FELIX – a flexible text-editing approach for generation, designed to derive maximum benefit from the ideas of decoding with bi-directional contexts and self-supervised pretraining. In contrast to conventional …...

AbstractWe present the results of the 6th round of the WMT task on MT Automatic Post-Editing. The task consists in automatically correcting the output of a “black-box” machine translation system …...

AbstractThe paper presents the submission by HW-TSC in the WMT 2020 Automatic Post Editing Shared Task. We participate in the English-German and English-Chinese language pairs. Our system is built based …...

AbstractMachine Translation (MT) is one of the most important natural language processing applications. Independently of the applied MT approach, a MT system automatically generates an equivalent version (in some target …...

AbstractIn automatic post-editing (APE) it makes sense to condition post-editing (pe) decisions on both the source (src) and the machine translated text (mt) as input. This has led to multi-encoder …...

AbstractAutomatic Post-Editing (APE) aims to correct errors in the output of a given machine translation (MT) system. Although data-driven approaches have become prevalent also in the APE task as in …...

AbstractAutomatic post-editing (APE) models are usedto correct machine translation (MT) system outputs by learning from human post-editing patterns. We present the system used in our submission to the WMT’21 Automatic …...

AbstractThis paper describes Netmarble’s submission to WMT21 Automatic Post-Editing (APE) Shared Task for the English-German language pair. First, we propose a Curriculum Training Strategy in training stages. Facebook Fair’s WMT19 …...

AbstractMulti-source sequence generation (MSG) is an important kind of sequence generation tasks that takes multiple sources, including automatic post-editing, multi-source translation, multi-document summarization, etc. As MSG tasks suffer from the …...

AbstractAutomatic post-editing (APE) refers to a research field that aims to automatically correct errors included in the translation sentences derived by the machine translation system. This study has several limitations, …...

AbstractThis paper describes IIT Bombay’s submission to the WMT22 Automatic Post-Editing (APE) shared task for the English-Marathi (En-Mr) language pair. We follow the curriculum training strategy to train our APE …...

AbstractWe present MLQE-PE, a new dataset for Machine Translation (MT) Quality Estimation (QE) and Automatic Post-Editing (APE). The dataset contains annotations for eleven language pairs, including both high- and low-resource …...