Opendata, web and dolomites

Bergamot SIGNED

Browser-based Multilingual Translation

Total Cost €

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EC-Contrib. €

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Partnership

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Project "Bergamot" data sheet

The following table provides information about the project.

Coordinator
THE UNIVERSITY OF EDINBURGH 

Organization address
address: OLD COLLEGE, SOUTH BRIDGE
city: EDINBURGH
postcode: EH8 9YL
website: www.ed.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 2˙999˙096 €
 EC max contribution 2˙999˙096 € (100%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2018-2
 Funding Scheme RIA
 Starting year 2019
 Duration (year-month-day) from 2019-01-01   to  2021-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE UNIVERSITY OF EDINBURGH UK (EDINBURGH) coordinator 983˙383.00
2    MZ DENMARK GMBH DE (BERLIN) participant 582˙387.00
3    THE UNIVERSITY OF SHEFFIELD UK (SHEFFIELD) participant 542˙187.00
4    UNIVERZITA KARLOVA CZ (PRAHA 1) participant 478˙012.00
5    TARTU ULIKOOL EE (TARTU) participant 413˙125.00
6    MZ DENMARK APS DK (KOBENHAVN) participant 0.00

Map

 Project objective

The Bergamot project will add and improve client-side machine translation in a web browser. Unlike current cloud-based options, running directly on users' machines empowers citizens to preserve their privacy and increases the uptake of language technologies in Europe in various sectors that require confidentiality. Free software integrated with an open-source web browser, such as Mozilla Firefox, will enable bottom-up adoption by non-experts, resulting in cost savings for private and public sector users who would otherwise procure translation or operate monolingually. To understand and support non-expert users, our user experience work package researches their needs and creates the user interface. Rather than simply translating text, this interface will expose improved quality estimates, addressing the rising public debate on algorithmic trust. Building on quality estimation research, we will enable users to confidently generate text in a language they do not speak, enabling cross-lingual online form filling. To improve quality overall, dynamic domain adaptation research addresses the peculiar writing style of a website or user by adapting translation on the fly using local information too private to upload to the cloud. These applications require adaptation and inference to run on desktop hardware with compact model downloads, which we address with neural network efficiency research. Our combined research on user experience, domain adaptation, quality estimation, outbound translation, and efficiency support a broad browser-based innovation plan.

 Publications

year authors and title journal last update
List of publications.
2019 Tereza Vojtěchová, Michal Novák, Miloš Klouček, Ondřej Bojar
SAO WMT19 Test Suite: Machine Translation of Audit Reports
published pages: 481-493, ISSN: , DOI: 10.18653/v1/w19-5355
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) 2019-10-07
2019 Erick Fonseca, Lisa Yankovskaya, André F. T. Martins, Mark Fishel, Christian Federmann
Findings of the WMT 2019 Shared Tasks on Quality Estimation
published pages: 1-10, ISSN: , DOI: 10.18653/v1/w19-5401
Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2) 2019-10-07
2019 Jindřich Helcl, Jindřich Libovický, Martin Popel
CUNI System for the WMT19 Robustness Task
published pages: 539-543, ISSN: , DOI: 10.18653/v1/w19-5364
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) 2019-10-07
2019 Rachel Bawden, Nikolay Bogoychev, Ulrich Germann, Roman Grundkiewicz, Faheem Kirefu, Antonio Valerio Miceli Barone, Alexandra Birch
The University of Edinburgh’s Submissions to the WMT19 News Translation Task
published pages: 103-115, ISSN: , DOI: 10.18653/v1/w19-5304
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) 2019-10-07
2019 Elizaveta Yankovskaya, Andre Tättar, Mark Fishel
Quality Estimation and Translation Metrics via Pre-trained Word and Sentence Embeddings
published pages: 101-105, ISSN: , DOI: 10.18653/v1/w19-5410
Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2) 2019-10-07
2019 Tom Kocmi, Ondřej Bojar
CUNI Submission for Low-Resource Languages in WMT News 2019
published pages: 234-240, ISSN: , DOI: 10.18653/v1/w19-5322
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) 2019-10-07
2019 Andre Tättar, Elizaveta Korotkova, Mark Fishel
University of Tartu’s Multilingual Multi-domain WMT19 News Translation Shared Task Submission
published pages: 382-385, ISSN: , DOI: 10.18653/v1/w19-5342
Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1) 2019-10-07

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The information about "BERGAMOT" are provided by the European Opendata Portal: CORDIS opendata.

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