This paper presents the Music Event Emotion Tracking (MEET) Metaverse, which is one of the demo results produced within the FUN-Media project. The MEET Metaverse is a virtual disco where multiple users can join together through their avatars to enjoy musical events. The peculiar characteristic of the MEET Metaverse is that the emotions of participants are inferred from their facial expressions and speech, and are used to select the next song to be played in the disco based on the average emotional state of participants. Moreover, avatars' facial poses are updated based on participants' emotions, and realistic avatar animations are reproduced using a combination of motion retargeting and high-fidelity appearance modeling.

MEET: the music event emotion tracking metaverse

Atzori, Luigi;Bingol, Gulnaziye;Floris, Alessandro;
2025-01-01

Abstract

This paper presents the Music Event Emotion Tracking (MEET) Metaverse, which is one of the demo results produced within the FUN-Media project. The MEET Metaverse is a virtual disco where multiple users can join together through their avatars to enjoy musical events. The peculiar characteristic of the MEET Metaverse is that the emotions of participants are inferred from their facial expressions and speech, and are used to select the next song to be played in the disco based on the average emotional state of participants. Moreover, avatars' facial poses are updated based on participants' emotions, and realistic avatar animations are reproduced using a combination of motion retargeting and high-fidelity appearance modeling.
2025
979-8-3315-5435-4
979-8-3315-5436-1
Avatar Rendering
Facial Emotion Recognition
Metaverse
Speech Emotion Recognition
Virtual Reality
File in questo prodotto:
File Dimensione Formato  
[pub] MEET_The_Music_Event_Emotion_Tracking_Metaverse.pdf

Solo gestori archivio

Descrizione: VoR
Tipologia: versione editoriale (VoR)
Dimensione 2.78 MB
Formato Adobe PDF
2.78 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
469451_AAM.pdf

accesso aperto

Descrizione: AAM
Tipologia: versione post-print (AAM)
Dimensione 3.51 MB
Formato Adobe PDF
3.51 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/469451
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact