Affectiva uses AI to analyze facial expressions and vocal tones. It helps understand human emotions in real-time, useful for marketing and automotive industries.
Kairos uses AI for facial recognition and emotion analysis. It helps detect emotions from video, photo, and even live streams, aiding in security and market research.
FaceReader by Noldus uses AI to analyze facial expressions. It provides insights into emotions like happiness, sadness, and anger, useful for psychological studies and consumer behavior research.
Beyond Verbal uses AI to analyze vocal intonations. It can detect emotions from voice, helping in customer service and mental health monitoring.
Developed by MIT Media Lab, Emotion AI uses machine learning to recognize emotions from facial expressions and physiological signals, supporting advanced research in emotional intelligence.
It uses AI to detect emotions from images. It identifies emotions like anger, contempt, fear, and happiness, aiding in various applications from gaming to user experience research.
IBM Watson Tone Analyzer uses AI to understand emotions and tones in written text. It helps in analyzing customer feedback and improving communication strategies.
It uses emotion recognition to monitor driver and passenger states, enhancing safety and comfort in vehicles by detecting drowsiness, distraction, and mood.
Cogito uses AI to analyze voice signals during phone calls. It provides real-time emotional intelligence to improve customer service interactions and employee engagement.