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AI Analyzes Emotions via Voice and Face
Russian researchers developed a multimodal neural network capable of analyzing signals related to human behavior and emotions by integrating data from voice, facial expressions, body language, and gaze. The goal is to identify emotional states and assess personality traits. Unlike emotion recognition systems that focus on a single indicator, this model relies on analyzing multiple signals to obtain a more accurate picture of emotional and behavioral states. It uses data from various sources to detect inconsistencies and fluctuations in reactions. In the future, this technology could be applied in digital education, intelligent interfaces, and user support services, helping to tailor interactions based on the user's emotional state and to analyze signs of confusion or hesitation.
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