Year: 2025
Type: article
Abstract: — Emotion-based music recommendation systems improve user experience by suggesting songs that reflect the listener’s mood. Techniques such as deep learning, facial emotion recognition, and wearable sensors to capture emotions from facial expressions, heart rate, or other signals are used. Convolutional Neural Networks (CNNs) isolate features from images for accurate emotion classification, while probabilistic models like Bayesian networks interpret uncertain emotions. By combining real-time emotion detection with recommendation algorithms, the system personalizes playlists instantly based on the user’s emotional state. This ensures a seamless and emotionally engaging listening experience for users.
DOI: 10.55041/ijsrem53038
Institution: Jawaharlal Nehru New College of Engineering
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4415149884
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