Emotion Based Music Playlist Recommendation System using Interactive Chatbot

Music is an integral part of our lives. However, since the social media platforms like TikTok and Instagram have a huge influence on the music charts worldwide, users are exposed solely to mainstream music, therefore the recommendations on music streaming platforms are not very personalized. An emotion-based recommendation system permits the users to listen to music based on their emotions. Existing systems use audio signals using the CNN approach
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and collaborative filtering
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to recommend songs based on the user's history. The proposed research work develops a personalized system, where the user's current emotion is analyzed with the help of the chatbot. The chatbot identifies the user's sentiment by asking some general questions. Based on the input provided by the user, a score is generated for each response, which adds up to a final score; this score is used to generate the playlist. The proposed recommendation system utilizes the Spotify platform and API for the playlist generation and recommendation.