Paper Title
Adaptive Music Recommendations Based on Real-Time Mood Detection
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Registration ID: IJNRD_226533
Published ID: IJNRD2408264
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Keywords
Face Authentication, Image Editing, Computational Vision, Mood Recognition.
Abstract
In the modern era, where technology seamlessly integrates with daily life, the enduring power of music as a medium for emotional expression and solace remains profound. "MOODY BLUES" is an innovative project that bridges the gap between emotion and music by introducing a facial emotion-based music recommendation system. This system leverages real-time emotion recognition to curate personalized and emotionally resonant listening experiences. Central to the project is a sophisticated emotion detection algorithm, utilizing deep learning and computer vision techniques to interpret users' emotions from their facial expressions. User profiles, which encompass music preferences, listening history, and emotional feedback, serve as the foundation for crafting dynamic, real-time music recommendations. Integration with popular music streaming platforms ensures a seamless transition from recommendations to listening. The project prioritizes privacy and ethical data handling, providing users with control and transparency over their data. A robust feedback loop allows users to influence their musical journey, refining future suggestions based on ratings and comments. "MOODY BLUES" aims to reshape the landscape of music recommendation by harmonizing with the ebb and flow of human emotions, highlighting the potential of technology to enhance the emotional richness of our lives.
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How To Cite (APA)
Vrushali D. Dharmale, Neha Kale, Saumitra Chaubey, Sanjana Molawade, & Rushikesh Gondane,Arnav Kadam (August-2024). Adaptive Music Recommendations Based on Real-Time Mood Detection. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(8), c572-c575. https://ijnrd.org/papers/IJNRD2408264.pdf
Issue
Volume 9 Issue 8, August-2024
Pages : c572-c575
Other Publication Details
Paper Reg. ID: IJNRD_226533
Published Paper Id: IJNRD2408264
Research Area: Computer Science & TechnologyÂ
Author Type: Indian Author
Country: Airoli, Navi Mumbai. Dist: Thane , Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2408264.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2408264
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