• Ch.Sahasra
• S.Karthik
• E.Deepthi
• L.Mankthu

In the modern era, human feeling is extremely important. Human feelings, which can be expressed or not, are the foundation of emotion. Emotion conveys a person's unique behavior, which can take many various shapes. Extraction of emotions reveals a person's unique behavioral state. This study aims to identify emotions and extract facial features from people. Same, to play music in accordance with the emotions found. Modern music services make it simple to access a lot of music. They are continuously trying to enhance music organization and search management, which will address the problem of choice and make discovering new musical works easier. More and more individuals are using recommendation algorithms to choose the right music for any situation. Personalization and recommendations based on emotions are still lacking, though. Humans are greatly influenced by music, which is frequently used to unwind, regulate mood, combat stress and disease, and sustain mental and physical activity. There are many different therapeutic venues and methods used in music therapy to enhance wellbeing. This essay will outline the construction of a system for recommending music based on the feelings, emotions, and activity contexts of the listener. A suggestion system is made to assist people in choosing music for a variety of circumstances and preserve their mental and bodily states by combining artificial intelligence methods and generalized music therapy methodologies.

Emotion Recognition, Music recommendation, Facial Extraction.

"A Facial Expression Recognition Using Convolutional Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 12, page no.d631-d634, December-2022, Available :http://www.jetir.org/papers/JETIR2212383.pdf

"A Facial Expression Recognition Using Convolutional Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 12, page no. ppd631-d634, December-2022, Available at : http://www.jetir.org/papers/JETIR2212383.pdf