Mood Based Music Recommendation System

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Anubhav Kumar; Anshu Sharma; Abhishek; Aditya Rajpoot; Aditya Singh; Ayushi Chaudhary

Mood Based Music Recommendation System

Authors: Anubhav Kumar, Anshu Sharma, Abhishek, Aditya Rajpoot, Aditya Singh, Ayushi Chaudhary

Unique Paper ID: 164818
Volume: 10
Issue: 12
PageNo: 2262-2268

Keywords: Face Recognition Image Processing Computer Vision Emotion Detection Music Mood Detection Content-Based Filtering Mental Health Machine Learning.

Abstract:
Psychological research has demonstrated that music effectively relieves stress, elevates mood, and triggers the release of neurochemicals such as oxytocin, serotonin, and dopamine. Consequently, music is widely utilized in therapeutic settings and rehabilitation centers for various disorders. As global mental health issues escalate, it is increasingly critical to address these concerns with innovative solutions. Existing music recommendation systems are inadequate in holistically addressing user needs, with few offerings mood-based recommendations and even fewer integrating therapeutic benefits tailored to specific situations. Given the widespread reliance on music for enhancing cognition, memory, and sleep quality, while reducing anxiety, pain, and blood pressure, there is a pressing need for a comprehensive product that maximizes these benefits. Our proposed system introduces a mood-based music player that performs real-time mood detection and recommends songs accordingly, enhancing traditional music player apps with this additional feature. This system aims to analyze user images, predict emotional expressions, and suggest suitable music, thereby improving user satisfaction and overall mental health.

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Cite This Article

ISSN: 2349-6002
Volume: 10
Issue: 12
PageNo: 2262-2268

Mood Based Music Recommendation System

Available:https://ijirt.org/article?manuscript=164818

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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