Intercultural Affect Recognition

Intercultural affect recognition focuses on developing artificial intelligence systems capable of accurately identifying emotions across diverse cultural backgrounds, addressing the limitations of current systems trained primarily on data from a single culture. Recent research emphasizes the development of robust multimodal models, often incorporating audio-visual data and leveraging techniques like attention-based feature selection, to improve cross-cultural accuracy. This field is crucial for building more inclusive and effective human-computer interaction systems, particularly in applications requiring understanding of emotional expression in diverse populations.