Project description
Understanding how mental lexicon across sign languages works
Sign language uses visual symbols to depict objects and actions. Unlike spoken words, signs are encoded into simultaneous units of form. How signers store these richly symbolic words in their mental lexicons is unclear. However, understanding this is crucial for creating better sign language resources. The ERC-funded SemaSign project uses computational methods to find correspondences between the form and meaning of sign languages. The project will create semantic networks for sign languages from Germany, Guinea-Bissau, and Kenya, by analysing word association responses to help identify clusters of unusually close signs in form and meaning. It will also investigate how lexicons emerge and grow early, especially in Guinea-Bissau, where the language is 15 years old.
Objective
Words in sign languages are rich in visual meaning. They contain shapes, movements, relations in space, etc. that depict objects and actions as symbolic metaphors; e.g. the action of pulling words out of the head in one language means ‘to ponder’. Yet, signs are also encoded into units of form that are articulated in simultaneous constructions, unlike sequences of consonants and vowels in spoken words. How, then, do signers store richly symbolic words that occur in highly simultaneous forms in their mental lexicons? At present, insight into these mental mappings remains highly occluded, not only at the level of behavioral and neural phenomena, but in terms of linguistic analysis as well. What, indeed, is morphology in sign languages when even the smallest units of form—like hooked fingers or a location at the throat—can carry meaning? What is the nature of these units? Do they vary across sign languages or are the iconic roots of form-meaning mappings so powerful that the same ones re-occur across unrelated sign languages? Answering these questions is urgently needed to create better sign language resources for teaching and learning, and to advance language technologies.
The SemaSign project proposes a ground-breaking approach to these questions by locating form-meaning correspondences in sign languages through computational means while creating new empirically-robust datasets to reveal how signs are organized in the mental lexicon. Semantic networks are created for sign languages from Germany, Kenya, and Guinea Bissau on the basis of word association responses in which a signer sees a sign from their language and responds with the first three signs that come to mind. This will establish an objective measure of semantic relatedness, enabling computational means to locate clusters of signs unusually close in both form and meaning. As the language in Guinea Bissau was formed only 15 years ago, we will also discover how lexicons emerge and grow at a very early stage
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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HORIZON.1.1 - European Research Council (ERC)
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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.
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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.
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Call for proposal
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(opens in new window) ERC-2023-STG
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20148 Hamburg
Germany
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