Objective
Rapid translation between European languages is a cornerstone of good governance in the EU, and of great academic and commercial interest. Statistical approaches to machine translation constitute the state-of-the-art. The basic knowledge source is a parallel corpus, texts and their translations. For domains where large parallel corpora are available, such as the proceedings of the European Parliament, a high level of translation quality is reached. However, in countless other domains where large parallel corpora are not available, such as medical literature or legal decisions, translation quality is unacceptably poor.
Domain adaptation as a problem of statistical machine translation (SMT) is a relatively new research area, and there are no standard solutions. The literature contains inconsistent results and heuristics are widely used. We will solve the problem of domain adaptation for SMT on a larger scale than has been previously attempted, and base our results on standardized corpora and open source translation systems.
We will solve two basic problems. The first problem is determining how to benefit from large out-of-domain parallel corpora in domain-specific translation systems. This is an unsolved problem. The second problem is mining and appropriately weighting knowledge available from in-domain texts which are not parallel. While there is initial promising work on mining, weighting is not well studied, an omission which we will correct. We will scale mining by first using Wikipedia, and then mining from the entire web.
Our work will lead to a break-through in translation quality for the vast number of domains with less parallel text available, and have a direct impact on SMEs providing translation services. The academic impact of our work will be large because solutions to the challenge of domain adaptation apply to all natural language processing systems and in numerous other areas of artificial intelligence research based on machine learning approaches.
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: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- humanities languages and literature general language studies
- social sciences sociology governance
- natural sciences computer and information sciences data science natural language processing
- natural sciences computer and information sciences artificial intelligence machine learning
- natural sciences computer and information sciences artificial intelligence heuristic programming
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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.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
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.
ERC-STG - Starting Grant
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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) ERC-2014-STG
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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.
80539 MUNCHEN
Germany
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.