Predicting affective engagement and mental strain from prosodic speech features

This research introduces a novel approach for assessing Positive Affective Engagement (as a proxy for emotional resilience) and Perceived Mental Strain (as a proxy for cognitive load) through speech prosody, highlighting the significant impact of language-specific variations. By combining prosodic features with machine learning techniques, the study offers a promising alternative to traditional psychological assessments. The findings emphasize the need for tailored, multilingual models to accurately estimate psychological states, with potential applications in mental health monitoring, cognitive workload analysis, and human-computer interaction. This work lays the foundation for future innovations in speech-based psychological profiling, advancing our understanding of human emotional and cognitive states in diverse linguistic contexts.