• Maddipati Lasya Mounika
• Godi Prasanth Kumar
• Ambati Ramya
• Burabathula Vamsi
• Angara Vaishnavi

Because of the rapid increase in digital information available, recommendation has grown to be a significant topic of research. Listening to music is a highly individual and situational habit for modern people who bring smartphones with them everywhere they go. This motivated us to propose the music recommendation system based on emotion recognition in this we are using mainly two algorithms which are Haar Cascade and Fisher Face. By using the in-built camera,the facial expressions are captured and to detect the emotions feature extraction is performed on the input emotions such as happy, sad, angry, surprise, and neutral. After detecting the emotions, then A user's current emotion is used to automatically create music. In terms of processing time, it performs better than the algorithm found in the literature..Our suggested system tends to decrease the system's overall cost and processing time required to produce the results, improving the system's overall correctness.

Music Recommendation, Feature Extraction, Emotion, Haar Cascade and Fisher Face

"Music Recommendation based on Emotion using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.b542-b547, March-2024, Available :http://www.jetir.org/papers/JETIR2403164.pdf

"Music Recommendation based on Emotion using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppb542-b547, March-2024, Available at : http://www.jetir.org/papers/JETIR2403164.pdf