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Found 26 papers, 0 papers with code
Shata-Anuvadak: Tackling Multiway Translation of Indian Languages
We present a compendium of 110 Statistical Machine Translation systems built from parallel corpora of 11 Indian languages belonging to both Indo-Aryan and Dravidian families.
Online Automatic Post-editing for MT in a Multi-Domain Translation Environment
Automatic post-editing (APE) for machine translation (MT) aims to fix recurrent errors made by the MT decoder by learning from correction examples.
eSCAPE: a Large-scale Synthetic Corpus for Automatic Post-Editing
eSCAPE consists of millions of entries in which the MT element of the training triplets has been obtained by translating the source side of publicly-available parallel corpora, and using the target side as an artificial human post-edit.
Selecting Machine-Translated Data for Quick Bootstrapping of a Natural Language Understanding System
The goal is to decrease the cost and time needed to get an annotated corpus for the new language, while still having a large enough coverage of user requests.
Findings of the WMT 2018 Shared Task on Automatic Post-Editing
In the former subtask, characterized by original translations of lower quality, top results achieved impressive improvements, up to -6. 24 TER and +9. 53 BLEU points over the baseline {``}\textit{do-nothing}{''} system.
Findings of the WMT 2019 Shared Task on Automatic Post-Editing
Seven teams participated in the English-German task, with a total of 18 submitted runs.
Automatic Post-Editing for Machine Translation
Automatic Post-Editing (APE) aims to correct systematic errors in a machine translated text.
Empirical Evaluation of Active Learning Techniques for Neural MT
Finally, we propose a neural extension for an AL sampling method used in the context of phrase-based MT - Round Trip Translation Likelihood (RTTL).
Instance Selection for Online Automatic Post-Editing in a multi-domain scenario
In recent years, several end-to-end online translation systems have been proposed to successfully incorporate human post-editing feedback in the translation workflow.
Findings of the 2021 Conference on Machine Translation (WMT21)
This paper presents the results of the newstranslation task, the multilingual low-resourcetranslation for Indo-European languages, thetriangular translation task, and the automaticpost-editing task organised as part of the Con-ference on Machine Translation (WMT) 2021. In the news task, participants were asked tobuild machine translation systems for any of10 language pairs, to be evaluated on test setsconsisting mainly of news stories.
FBK’s Neural Machine Translation Systems for IWSLT 2016
They leverage linguistic information such as lemmas and part-of-speech tags of the source words in the form of additional factors along with the words.
Findings of the WMT 2020 Shared Task on Automatic Post-Editing
Due to i) the different source/domain of data compared to the past (Wikipedia vs Information Technology), ii) the different quality of the initial translations to be corrected and iii) the introduction of a new language pair (English-Chinese), this year’s results are not directly comparable with last year’s round.
