Emotional AI: How Machines are Learning to Understand our Feelings
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Affective computing integrates computer science, engineering, psychology, and neuroscience to enable machines to understand and respond to human emotions in real-time interactions.
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Research output in affective computing grew steadily from 1997-2019, driven recently by deep learning advancements, with China, the U.S., and India as top contributors.
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Current trends include creating multimodal emotion datasets, advancing multimodal fusion to combine facial, vocal, textual cues, and applying affective computing in virtual reality, empathic dialogues, and more emotionally intelligent technologies.
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Future applications show promise in healthcare, entertainment, education, business services, and integrating science and art by leveraging machines' emotional intelligence.
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As the field expands, ethical considerations around emotional data privacy and developing international standards are being addressed.