• Mr. Rikin Zala
• Mr. Harsh Thakkar
• Mr. Jaynil Zala
• Prof. Babita Patel

An advanced Emotion-based Music Recommendation System is proposed, leveraging Speech Emotion Recognition (SER), Speech-Text Emotion Recognition (TER). The Convolutional Neural Networks (CNNs) model categorizes songs based on user’s emotional states - angry, happiness, calmness and sadness, integrates with music streaming platforms (Spotify), and features a user-friendly interface for personalized music discovery. With music generation (EMOPIA) capabilities and ongoing recommendation refinement, this system aims to revolutionize music engagement by resonating with individual emotions and preferences.

Emotion Recognition, Convolutional Neural Networks, Music Recommendation, Music Generation, Valence-Arousal mapping.

"Research Paper on Emotion Based Music Recommendation using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.h340-h347, April-2024, Available :http://www.jetir.org/papers/JETIR2404743.pdf

"Research Paper on Emotion Based Music Recommendation using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. pph340-h347, April-2024, Available at : http://www.jetir.org/papers/JETIR2404743.pdf