Project description
Improving neural machine translation for low-resource language
In a world where accurate and timely information has become imperative, journalists are in constant need of the appropriate tools of fast and accurate translation for languages with very few resources. Although neural machine translation technology advances rapidly, it has not managed yet to deliver usable translations for most language pairs in the world due to the lack of data and parallel corpora. The EU-funded GoURMET aims at improving the robustness and applicability of neural machine translation for low-resource language pairs and domains. The project will focus on global content creation by providing machine translations for correction by humans and on international news media monitoring for low-resource language pairs.
Objective
Machine translation (MT) is an increasingly important technology for supporting communication in a globalised world. MT technology has gradually increased over the last ten years, but recent advances in neural machine translation (NMT), have resulted in significant interest in industry and have lead to very rapid adoption of the new paradigm (eg. Google, Facebook, UN, World International Patent Office). Although these models have shown significant advances in state-of-the-art performance they are data intensive and require parallel corpora of many millions of human translated sentences for training. Neural Machine translation is currently not able to deliver usable translations for the vast majority of language pairs in the world. This is especially problematic for our user partners, the BBC and DW who need access to fast and accurate translation for languages with very few resources.
The aim of GoURMET is to significantly improve the robustness and applicability of neural machine translation for low-resource language pairs and domains.
GoURMET has five objectives:
- Development of a high-quality machine translation for under-resourced language pairs and domains;
- Adaptable to new and emerging languages and domains;
- Development of tools for analysts and journalists;
- Sustainable, maintainable platform and services;
- Dissemination and communication of project results to stakeholders and user group.
The project will focus on two use cases:
- Global content creation - managing content creation in several languages efficiently by providing machine translations for correction by humans;
- Media monitoring for low resource language pairs - tools to address the challenge of international news monitoring problem.
The outputs of the project will be field-tested at partners BBC and DW, and the platform will be further validated through innovation intensives such as the BBC NewsHack.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.1.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
RIA - Research and Innovation action
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-ICT-2018-20
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
EH8 9YL Edinburgh
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.