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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM35259

MUSIC RECOMMENDATION SYSTEM USNG FACIAL RECOGNITION

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM35259

Volume:

8 |

5 |

May 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PS

Pranav Sonawane

PS

Pranil Sonawane

AM

Abhijit More

AM

Ashutosh Munde

PJ

Prof.Rupali Jadhav

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Abstract

it could be exceptionally dumbfounding for individuals to pick which track to tune in to from a wide run of selections to be had. one-of-a-kind proposition systems were made for precise areas like track, devouring, and buying, catering to the consumer’s slants. Our fundamental goal is to supply track proposals that adjust with the consumer’s flavor. via analyzing facial expressions and customer sentiments, prepared to select up encounters into their contemporary mental or keen state. song and recordings provide a superb possibility to appear clients with a excellent variety of selections based totally on their inclines and beyond facts. it’s far properly recognized that human beings make make use of of facial expressions to specific more without a doubt what they want to say and the putting wherein they implied their phrases. greater than 60 percentage of the customers be given that at a positive factor of time the wide variety of melodies show of their tunes library is so massive that they’re incapable to figure out the tune which they got to play. through growing a suggestion framework, it appear assist a purchaser to form a preference with recognize to which tune one ought to track in to making a distinction the consumer to decrease his/her push tiers. The purchaser would now not were given to squander any time in searching or to peer up for melodies and the leading music coordinating the user’s disposition is identified, and tunes would be regarded to the patron concurring to his/her disposition. The photo of the client is captured with the assistance of a webcam. The consumer’s image is taken after which as per the temper/emotion of the customer an fitting melody from the playlist of the client is appeared coordinating the person’s prerequisite.

KEYWORDS

Music Recommendation System Facial Emotion Recognition Recommendation User Preferences Emotional States User Engagement..

Cite This Article

Pranav Sonawane, Pranil Sonawane, Abhijit More, Ashutosh Munde, Prof.Rupali Jadhav, "MUSIC RECOMMENDATION SYSTEM USNG FACIAL RECOGNITION," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 5, May 2024.

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Publication Date

12/31/45442

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Double-Blind Peer Review

Review Rounds: 2

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