EmoTune – Emotion Based Music Recommendation System Article Swipe
Pradeesh S
,
Hemalatha S
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.17875261
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.17875261
EmoTune is an AI-powered emotion recognition and music recommendation system that bridges the gap between human emotions and personalized music experiences. The project integrates deep learning, computer vision, and API-driven recommendation to detect human emotions from facial expressions and generate corresponding playlists using the Spotify API. A conversational chatbot powered by the Groq API adds empathetic interaction, allowing users to express feelings and receive suggestions naturally. Built using React, TailwindCSS, and FastAPI, the system provides a smooth and responsive user experience. EmoTune demonstrates how artificial intelligence can be leveraged to build emotionally intelligent systems that enhance user engagement through real-time emotion understanding and adaptive personalization.
Related Topics
Concepts
Recommender system
Chatbot
Computer science
Feeling
Human–computer interaction
Emotion recognition
Multimedia
Affective computing
Dialog system
Emotion classification
World Wide Web
Personalization
Artificial intelligence
Facial expression
Collaborative filtering
Emotion detection
Key (lock)
User modeling
The Internet
Deep learning
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.5281/zenodo.17875261
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W7114777446
All OpenAlex metadata
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https://openalex.org/W7114777446Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5281/zenodo.17875261Digital Object Identifier
- Title
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EmoTune – Emotion Based Music Recommendation SystemWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-12-10Full publication date if available
- Authors
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Pradeesh S, Hemalatha SList of authors in order
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https://doi.org/10.5281/zenodo.17875261Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://doi.org/10.5281/zenodo.17875261Direct OA link when available
- Concepts
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Recommender system, Chatbot, Computer science, Feeling, Human–computer interaction, Emotion recognition, Multimedia, Affective computing, Dialog system, Emotion classification, World Wide Web, Personalization, Artificial intelligence, Facial expression, Collaborative filtering, Emotion detection, Key (lock), User modeling, The Internet, Deep learningTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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