Emotion Analysis

Emotion Analysis (Affective Computing) uses AI to detect and interpret human emotional states—like joy, anger, or fear—from multimodal data (facial expressions, vocal tone, and text).

This technology employs machine learning (ML) and Natural Language Processing (NLP) to classify specific human emotions from vast data streams. Systems like IBM Watson analyze text for keywords; computer vision models track over 130 facial expression detections in real-time. The core value: translating subtle, non-verbal cues into actionable data for business applications (e.g., improving Customer Experience, or CX) and research. Accuracy rates for emotion recognition from speech can reach 70%, surpassing human performance (around 60%): this drives smarter, more empathetic human-computer interaction.

https://www.media.mit.edu/groups/affect/overview/