Opendata, web and dolomites

MOVES SIGNED

MOdelling Vocal Expression in Schizophrenia

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 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.

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

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.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "MOVES" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.1.3.2.)

SSHelectPhagy (2019)

Regulation of Selective autophagy by sulfide through persulfidation of protein targets.

Read More  

RipGEESE (2020)

Identifying the ripples of gene regulation evolution in the evolution of gene sequences to determine when animal nervous systems evolved

Read More  

PanILC (2019)

Deciphering type 2 innate lymphoid cell/epithelial progenitor cell crosstalk in pancreas regeneration and neoplasia

Read More