Objective
Recent years have witnessed the development of a wide range of computational methods that process and generate natural language text. Many of these have become familiar to mainstream computer users such as tools that retrieve documents matching a query, perform sentiment analysis, and translate between languages. Systems like Google Translate can instantly translate between any pair of over fifty human languages allowing users to read web content that wouldn't have otherwise been available. The accessibility of the web could be further enhanced with applications that translate within the same language, between different modalities, or different data formats. There are currently no standard tools for simplifying language, e.g. for low-literacy readers or second language learners. The web is rife with non-linguistic data (e.g. databases, images, source code) that cannot be searched since most retrieval tools operate over textual data. In this project we maintain that in order to render electronic data more accessible to individuals and computers alike, new types of models need to be developed. Our proposal is to provide a unified framework for translating from comparable corpora, i.e. collections consisting of data in the same or different modalities that address the same topic without being direct translations of each other. We will develop general and scalable models that can solve different translation tasks and learn the necessary intermediate representations of the units involved in an unsupervised manner without extensive feature engineering. Thanks to recent advances in deep learning, we will induce representations for different modalities, their interactions, and correspondence to natural language. Beyond addressing a fundamental aspect of the translation problem, the proposed research will lead to novel internet-based applications that simplify and summarize text, produce documentation for source code, and meaningful descriptions for images.
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.
- humanities languages and literature general language studies
- natural sciences computer and information sciences databases
- natural sciences computer and information sciences computational science
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
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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.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-COG - Consolidator 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-2015-CoG
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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.