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 natural sciencescomputer and information sciencessoftwareengineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsnatural sciencescomputer and information sciencesartificial intelligencemachine learning Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-PoC-2015 - ERC Proof of Concept Grant Call for proposal ERC-2015-PoC See other projects for this call Funding Scheme ERC-POC - Proof of Concept Grant Host institution AUDEERING GMBH Net EU contribution € 149 937,50 Address FRIEDRICHSHAFENER STRASSE 1 82205 Gilching Germany See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Bayern Oberbayern Starnberg Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 149 937,50 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all AUDEERING GMBH Germany Net EU contribution € 149 937,50 Address FRIEDRICHSHAFENER STRASSE 1 82205 Gilching See on map SME The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed. Yes Region Bayern Oberbayern Starnberg Activity type Private for-profit entities (excluding Higher or Secondary Education Establishments) Links Contact the organisation Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 149 937,50
