Affective Computing Has Changed: The Foundation Model Disruption
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.
Code (0)
등록된 구현이 없습니다.
Tasks
modelSimilar Papers 제목 키워드 기반
On Prompt Sensitivity of ChatGPT in Affective Computing
Recent studies have demonstrated the emerging capabilities of foundation models like ChatGPT in several fields, including affective computing. However, accessing these emerging capabilities is facilitated through prompt …
Prompt EngineeringSarcasm DetectionSensitivitySentiment Analysis+1Teleology-Driven Affective Computing: A Causal Framework for Sustained Well-Being
Affective computing has made significant strides in emotion recognition and generation, yet current approaches mainly focus on short-term pattern recognition and lack a comprehensive framework to guide affective agents t…
Emotion RecognitionMeta Reinforcement LearningExploring How Audio Effects Alter Emotion with Foundation Models
Audio effects (FX) such as reverberation, distortion, modulation, and dynamic range processing play a pivotal role in shaping emotional responses during music listening. While prior studies have examined links between lo…
A Wide Evaluation of ChatGPT on Affective Computing Tasks
With the rise of foundation models, a new artificial intelligence paradigm has emerged, by simply using general purpose foundation models with prompting to solve problems instead of training a separate machine learning m…
Aspect ExtractionSarcasm DetectionSentiment AnalysisA Comprehensive Survey on Affective Computing; Challenges, Trends, Applications, and Future Directions
As the name suggests, affective computing aims to recognize human emotions, sentiments, and feelings. There is a wide range of fields that study affective computing, including languages, sociology, psychology, computer s…
Mixed RealitySociologySurvey