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International Advanced Research Journal in Science, Engineering and Technology
International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal
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← Back to VOLUME 11, ISSUE 2, FEBRUARY 2024

Music Recommendation System

Kasar Jayesh, Bhosale Prerna, Supekar Gayatri, Khan Aun Irfan Mohd,Prof. Abhale B.A

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Abstract: Music plays a significant role in improving and elevating one's mood as it is one of the important source of entertainment and inspiration to move forward. Recent studies have shown that humans respond as well as react to music in a very positive manner and that music has a high impact on human's brain activity. Now a days, people often prefer to listen to music based on their moods and interests. This work focuses on a system that suggests songs to the users, based on their state of mind. In this system, computer vision components are used to determine the user's emotion through facial expressions. Once the emotion is recognized, the system suggests a song for that emotion, saving a lot of time for a user over selecting and playing songs manually. A user study is presented to evaluate the application. Results reveal good usability of the service and show that visualization and interaction in a music emotion space can improve acceptance of music recommendations. Cite: Kasar Jayesh, Bhosale Prerna, Supekar Gayatri, Khan Aun Irfan Mohd,Prof. Abhale B.A, "Music Recommendation System", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 2, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.13221.

How to Cite:

[1] Kasar Jayesh, Bhosale Prerna, Supekar Gayatri, Khan Aun Irfan Mohd,Prof. Abhale B.A, “Music Recommendation System,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.11221

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