Affective Computing Has Changed: The Foundation Model Disruption

Autor: Schuller, Björn, Mallol-Ragolta, Adria, Almansa, Alejandro Peña, Tsangko, Iosif, Amin, Mostafa M., Semertzidou, Anastasia, Christ, Lukas, Amiriparian, Shahin
Rok vydání: 2024
Předmět:
Druh dokumentu: Working Paper
Popis: The dawn of Foundation Models has on the one hand revolutionised a wide range of research problems, and, on the other hand, democratised the access and use of AI-based tools by the general public. We even observe an incursion of these models into disciplines related to human psychology, such as the Affective Computing domain, suggesting their affective, emerging capabilities. In this work, we aim to raise awareness of the power of Foundation Models in the field of Affective Computing by synthetically generating and analysing multimodal affective data, focusing on vision, linguistics, and speech (acoustics). We also discuss some fundamental problems, such as ethical issues and regulatory aspects, related to the use of Foundation Models in this research area.
Databáze: arXiv