Objective
The morphological structure of a word plays an important role in determining its function and meaning, yet it is often disregarded by current machine learning models aimed at natural language processing (NLP). State-of-the-art NLP models typically rely on word-level or character-level representations. This arguably works well for English, the dominant language in NLP research, since it is morphologically simple, but poses a challenge for morphologically-rich languages like Basque, Estonian, or Kurdish. As a consequence, the current state of the art is biased against these languages, preventing us from building better NLP technology for them.
The MorphIRe project aims to learn morphologically-informed representations for NLP. It proposes to explore the fine-grained morphological analysis of word forms in order to learn representations that are grounded in morphemes, the smallest grammatical unit of language. Using these representations as input to NLP models is expected to improve their performance particularly for morphologically-rich languages. To this end, MorphIRe will make use of deep learning with neural network architectures both to learn the representations and to apply them to state-of-the-art models for a variety of NLP tasks, such as language modelling and dependency parsing.
The impact of MorphIRe is twofold: 1) Learning input representations that can be used in a variety of models encourages reusability of the results and promises that improvements will carry over to future NLP research. 2) Through improving the state of the art on morphologically-rich languages, speakers of these languages will ultimately benefit from better NLP technology. This way, MorphIRe has the potential for making both a scientific and a societal impact.
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.
- natural sciences computer and information sciences data science natural language processing
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- natural sciences computer and information sciences artificial intelligence computational intelligence
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
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.
-
H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
See all projects funded under this programme -
H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
See all projects funded under this programme
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.
MSCA-IF-EF-ST - Standard EF
See all projects funded under this funding scheme
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-MSCA-IF-2018
See all projects funded under this callCoordinator
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.
1165 KOBENHAVN
Denmark
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.