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Predictive Music Based on Mood

Author

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  • Ganesh B. Regulwar
  • Nikhila Kathirisetty

Abstract

It is often difficult for a person to choose which mu- sic to listen to from a vast array of available options. Relatively, this paper focuses on building an efficient music recommendation system based on the user’s mood which determines the emotion of user using Facial Recognition technique. The model is build using the transfer learning approach for which MobileNet model and Cascade classifier are used. Analyzing the user’s face expression might help you better comprehend their current emotional or mental condition. Music and video are one area where there is a lot of potential to present clients with a variety of options depending on their interests and data. More than 60% of users anticipate that the number of songs in their music collection will grow to the point where they will be unable to find the song they need to play at some point in the future. The user would save time by not having to search for or look up tunes. The image of the user is captured using a webcam. Then, depending on the user’s mood, an appropriate song from the user’s playlist or a movie is shown.

Suggested Citation

  • Ganesh B. Regulwar & Nikhila Kathirisetty, 2024. "Predictive Music Based on Mood," International Journal of Scientific Research in Science, Engineering and Technology, Technoscience Academy, vol. 11(3), pages 74-81, May.
    • Handle: RePEc:ijs:ijsrse:v11:y2024:i3:id:99
    DOI: 10.32628/IJSRSET2411310
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