Findings of the 2019 conference on machine translation (WMT19)

L Barrault, O Bojar, MR Costa-Jussa, C Federmann… - 2019 - zora.uzh.ch
This paper presents the results of the premier shared task organized alongside the
Conference on Machine Translation (WMT) 2019. Participants were asked to build machine …

Findings of the 2017 conference on machine translation (wmt17)

O Bojar, R Chatterjee, C Federmann, Y Graham… - 2017 - doras.dcu.ie
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 …

A survey of orthographic information in machine translation

BR Chakravarthi, P Rani, M Arcan, JP McCrae - SN computer science, 2021 - Springer
Abstract Machine translation is one of the applications of natural language processing which
has been explored in different languages. Recently researchers started paying attention …

The effectiveness of morphology-aware segmentation in low-resource neural machine translation

J Sälevä, C Lignos - ar** and managing an etymological lexical resource: Introducing etymdb 2.0
C Fourrier, B Sagot - LREC 2020-12th Language Resources and …, 2020 - inria.hal.science
Diachronic lexical information was mostly used in its natural field, historical linguistics, until
recently, when promising but not yet conclusive applications to low resource languages …

The University of Helsinki submissions to the WMT19 news translation task

A Talman, U Sulubacak, R Vázquez, Y Scherrer… - arxiv preprint arxiv …, 2019 - arxiv.org
In this paper, we present the University of Helsinki submissions to the WMT 2019 shared
task on news translation in three language pairs: English-German, English-Finnish and …

Transfer learning and subword sampling for asymmetric-resource one-to-many neural translation

SA Grönroos, S Virpioja, M Kurimo - Machine Translation, 2020 - Springer
There are several approaches for improving neural machine translation for low-resource
languages: monolingual data can be exploited via pretraining or data augmentation; parallel …

[CITAZIONE][C] Leveraging orthographic information to improve machine translation of under-resourced languages

A Chakravarthi, B Raja - 2020 - NUI Galway