Objective
The automated sensing of human emotions has gained a lot of commercial attention lately. For facial and physiological sensing many companies offer first professional products. Recently, voice analytics has become a hot topic, too, with first companies emerging for the telecom, entertainment, and robot markets (e.g. Sympalog, Aldebaran, etc.). Current vocal emotion detection approaches rely on machine learning where emotions are identified based on a reference set of expression clips. The drawback of this method is the need to rely on a small set of basic, highly prototypical emotions. Real life emotion detection application fields such as clinical diagnosis, marketing research, media impact analysis, and forensics and security, require subtle differentiations of feeling states. VocEmoApI will develop a first-of-its-kind proof-of-concept software for vocal emotion detection based on a fundamentally different approach: Focusing on vocal nonverbal behavior and sophisticated acoustic voice analysis, it will exploit the building blocks of emotional processes. This approach will infer not only basic emotion categories but also much finer distinctions such as subcategories of emotion families and subtle emotions. The development of VocEmoApI draw’s extensively on the results of the applicant’s Advanced Grant, providing a solid theoretical basis. Market analysis through marketing research partners will be conducted and the prototype software will be utilized to promote the technology and estimate a product value based on feedback from industry contacts. Strong impact of VocEmoApI on large markets such as household robotics, public security, clinical diagnosis and therapy, call analytics, and marketing research can expected.
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 software
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics
- natural sciences computer and information sciences artificial intelligence machine learning
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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-POC - Proof of Concept 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-PoC
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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.
82205 Gilching
Germany
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.