• AMIT CHOWDARY KAMMA
• K M IMPANA
• MADHAN N
• MISMITHA S
• SHARMILA CHIDARAVALLI

Humans use their facial expressions as one means of expressing their emotions, which is a strong tool in communication. Recognizing facial expressions is one of the most difficult and effective jobs in social communication since facial expressions are crucial in non-verbal communication. In order to explain and comprehend human emotions, songs have always been a popular alternative. The expression of an individual's emotion can be seen in their eyes, cheeks, forehead, or even in the curve of their smile, among other facial features. Music is a sort of art that calms and soothes the human body and brain. Taking these two ideas and combining them, this project focuses on identifying an individual's emotion through their facial expression and playing music that will help them feel better or just calm down. It can also provide faster song selection based on their mood, saving time from searching through various songs, while simultaneously developing software that can be used anywhere with the functionality of playing music according to their mood. This study has the random forest algorithm which is a supervised machine learning. The result found are promising to have an accuracy of more than 89%.

Random forest algorithm, Feature extraction, Machine learning, Music therapy.

"SURVEY PAPER ON MUSIC PREDICTION AND THERAPY USING RANDOM FOREST", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.c587-c598, March-2023, Available :http://www.jetir.org/papers/JETIR2303266.pdf

"SURVEY PAPER ON MUSIC PREDICTION AND THERAPY USING RANDOM FOREST", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppc587-c598, March-2023, Available at : http://www.jetir.org/papers/JETIR2303266.pdf