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MOVES SIGNED

MOdelling Vocal Expression in Schizophrenia

Total Cost €

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EC-Contrib. €

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Partnership

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 MOVES project word cloud

Explore the words cloud of the MOVES project. It provides you a very rough idea of what is the project "MOVES" about.

mood    innovative    tool    fostered    voice    personality    mental    monitoring    limited    considerable    clinical    vocal    international    datasets    clinicians    cross    technologies    lack    schizophrenia    signal    relationship    models    area    atypicalities    emotion    artificial    foundations    psychiatry    translate    responsible    machine    emotional    computational    centric    collaborative    implications    diagnosis    science    screening    conceptualise    disorders    social    disentangle    overcome    powerful    impairment    collaborations    pioneers    patterns    human    revolution    neuroscience    abnormalities    intelligence    affective    cognitive    mechanisms    core    speaker    assist    technological    first    settings    atypical    limits    tend    moves    ai    infer    individuals    capture    intention    communication    linguistic    evaluations    create    symptoms    intersection    sz    tools    monitor    systematic    learning    regulation    capability    traits    solid    larger    poor    underlying   

Project "MOVES" data sheet

The following table provides information about the project.

Coordinator
AARHUS UNIVERSITET 

Organization address
address: NORDRE RINGGADE 1
city: AARHUS C
postcode: 8000
website: www.au.dk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Denmark [DK]
 Total cost 207˙312 €
 EC max contribution 207˙312 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2020
 Duration (year-month-day) from 2020-09-01   to  2022-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    AARHUS UNIVERSITET DK (AARHUS C) coordinator 207˙312.00

Map

 Project objective

The human voice is a powerful tool for social communication. In recent years, Artificial Intelligence (AI) fostered the development of advanced voice systems, able to infer considerable information from the speaker’s voice, such as emotional and mental states, mood information and personality traits. Individuals with schizophrenia (SZ) tend to present voice atypicalities, which are related to core clinical symptoms and social impairment. Recent advances in voice technology may lead the way to a revolution in the study of voice disorders. They may allow to disentangle the affective, cognitive and social mechanisms responsible for voice atypicalities, assist clinicians in diagnosis and monitoring of the disorders, and enhance their capability to capture the complex relationship between vocal behaviour, emotion regulation and clinical features. However, our present understanding of voice abnormalities in SZ is very poor, limited by the lack of comprehensive models and systematic approaches to study voice production. MOVES aims at providing a solid understanding of the implications of atypical voice patterns in SZ: through the application of machine learning and signal processing technologies (AI), I will provide a first comprehensive account of the mechanisms underlying voice atypicalities, assess their impact on clinical evaluations, and create the foundations for more reliable and evidence-based screening tools. The project aims to foster multi-centric and international collaborations to overcome important limits of this research field, such as the need for cross-linguistic studies, larger datasets, and open and collaborative research. MOVES pioneers a new area of research at the intersection between cognitive neuroscience, psychiatry, computational science and AI. An innovative aspect of the project is the intention to translate recent AI technological advances into clinical settings, to improve the way we conceptualise, assess and monitor voice disorders in SZ.

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The information about "MOVES" are provided by the European Opendata Portal: CORDIS opendata.

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