Emotional investigation has generated remarkable fascination, resulting in meticulous research with significant implications. In contrast to more comprehensive methods, which take into account multiple channels of emotion detection, traditional techniques often struggle to accommodate complex scenarios and diverse user groups due to their narrow focus. The expanding requirement for integrated emotional evaluation strategies, drawing on disparate sensory sources, can be linked to this upsurge. A comprehensive review of the progression, available choices, and outstanding concerns about multimodal emotion understanding is offered through this research. Investigating the most frequently utilized language modes, we evaluate their capacity to transmit sentiments and any inherent restrictions. Examining methods for combining diverse modalities reveals mysterious relationships between flexibility, nuance, and output. By exploring the varied uses of multi-modal emotion analysis, we demonstrate its inherent advantage over singular techniques. After carefully analyzing the key issues associated with emotional stability, persistent oscillations, and theoretical frameworks, and interpreting meaningful discoveries, we investigate the potential for further research on multi-modal emotion identification.

Multimodal Interfaces for Emotion Recognition: Models, Challenges and Opportunities

Greco D.;
2024-01-01

Abstract

Emotional investigation has generated remarkable fascination, resulting in meticulous research with significant implications. In contrast to more comprehensive methods, which take into account multiple channels of emotion detection, traditional techniques often struggle to accommodate complex scenarios and diverse user groups due to their narrow focus. The expanding requirement for integrated emotional evaluation strategies, drawing on disparate sensory sources, can be linked to this upsurge. A comprehensive review of the progression, available choices, and outstanding concerns about multimodal emotion understanding is offered through this research. Investigating the most frequently utilized language modes, we evaluate their capacity to transmit sentiments and any inherent restrictions. Examining methods for combining diverse modalities reveals mysterious relationships between flexibility, nuance, and output. By exploring the varied uses of multi-modal emotion analysis, we demonstrate its inherent advantage over singular techniques. After carefully analyzing the key issues associated with emotional stability, persistent oscillations, and theoretical frameworks, and interpreting meaningful discoveries, we investigate the potential for further research on multi-modal emotion identification.
2024
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
9783031606137
9783031606113
Affective computing
Emotion recognition
Multimodal interfaces
Signal processing
File in questo prodotto:
File Dimensione Formato  
978-3-031-60611-3_11-2.pdf

Accesso riservato

: Publisher’s version
Dimensione 195.07 kB
Formato Adobe PDF
195.07 kB 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/11311/1268127
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact