Emotion Based Music Playlist Recommendation System


Authors : K Aditya Shastry; Vikas Gowda M N

Volume/Issue : Volume 7 - 2022, Issue 7 - July

Google Scholar : https://bit.ly/3TmGbDi

Scribd : https://tinyurl.com/58adxtdp

DOI : https://doi.org/10.5281/zenodo.8395043

Abstract : Our lives anticipate music to play a significant role. However, because platforms for social media, like TikTok and Instagram have such a large influence on global music charts, consumers are only exposed to mainstream music, hence music streaming platform recommendations are not especially individualized. A recommendation algorithm based on emotions allows users to listen to music according to their emotions. Depending on the user's prior listening habits, current systems use audio and content - based filtering to make music suggestions. The suggested research project creates a tailored system that analysesthe user's current emotion. Ascore is generated for each response based on the user's input, which adds up to a total score, which is utilized to generate the playlist. For playlist production and suggestion, the suggested recommendation system makes use of the Spotify platform andAPI usingValance Arousal dataset training the datasets into k-means clustering.

Keywords : TikTok, Instagram, Recommendation system, Valance Arousal dataset and K-Means clustering.

Our lives anticipate music to play a significant role. However, because platforms for social media, like TikTok and Instagram have such a large influence on global music charts, consumers are only exposed to mainstream music, hence music streaming platform recommendations are not especially individualized. A recommendation algorithm based on emotions allows users to listen to music according to their emotions. Depending on the user's prior listening habits, current systems use audio and content - based filtering to make music suggestions. The suggested research project creates a tailored system that analysesthe user's current emotion. Ascore is generated for each response based on the user's input, which adds up to a total score, which is utilized to generate the playlist. For playlist production and suggestion, the suggested recommendation system makes use of the Spotify platform andAPI usingValance Arousal dataset training the datasets into k-means clustering.

Keywords : TikTok, Instagram, Recommendation system, Valance Arousal dataset and K-Means clustering.

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