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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.

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

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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