WP2
Natural voice processing
will investigate how neural systems in living organisms (humans, animals) and in artificial systems (machine) decode and represent socio-affective information and identity information expressed in voices.
WP3
Synthetic Voice Design
will focus on advancing our understanding of synthetic voice perception and optimizing voice synthesis technology.
WP4
Voice Applications
will transfer the basic knowledge gathered as part of WPs 2 and 3 into innovative user-oriented applications in two main domains: Health and Forensics.
With AI-driven advances, the rapidly developing field of voice technology (VT) has transformed European life through voice assistants, text-to-speech systems, and cochlear implants.
However, severe challenges remain in processing paralinguistic information such as identity, emotional state or health in voices.
The Voice Communication Sciences (VoCS) project is an ambitious initiative to address these challenges and advance Europe’s position at the forefront of VT. VoCS aims to train a new generation of scientists with interdisciplinary expertise in Voice Communication Sciences.
The project gathers a consortium of 21 academic and non-academic partners across 12 countries, collaborating to provide a world-class training-by-research program. The primary goal is to equip 17 doctoral candidates (DCs) with integrated knowledge spanning cognitive neuroscience, acoustics, phonetics, and computing science, via a unique combination of hands-on research training in labs, with cross-sectorial workshops in fundamental, technological, and clinical domains relevant to voice communication.
The project’s innovative aspects lie in its comprehensive approach to voice processing, bridging disciplines from neuroscience to engineering. The VoCS research program is structured around three scientific objectives: (1) advancing basic knowledge of natural voice processing, exploring paralinguistic information in voices; (2) building on these insights to design more natural and flexible synthetic voices; (3) transferring this knowledge into user-oriented applications in health and forensics, including the improvement of voice perception for hearing-impaired individuals, advancements in forensic speaker comparison methods, and the development of tools to combat deepfake speech.