• Naveeth Ahamed S
• Dr. R. N. Devendra Kumar
• Nandish K
• Kalaiyarasan M R

The growth of digital music platforms, personalized approval processes have become important to increase user engagement and satisfaction. Traditional recommendation models rely on information obtained from the user's listening history, preferences, or demographic information.However, these methods often fail to immediately transfer to the user's mind, which limits the depth of personalization. This study introduces a new aesthetic approach based on facial recognition and adapts music recommendations to the user's current mood. Model to experience various emotions such as happiness, sadness, anger, surprise, patience, etc. The system can reflect the user's mood by analyzing their face and recommend music that supports or improves their mood. This approach allows users to connect with the music they are listening to, as recommendations are related to experiences that are needed nearby, creating a more intuitive and productive experience. To achieve this, the project integrates facial analysis algorithms with a recommendation engine that detects the need for suitable songs or specific songs. The combination of deep learning and classification algorithms makes it more accurate in search theory and ensures that song recommendations are relevant and engaging for users. By capturing and responding to users’ emotions, the system plays a central role in the development of context-aware recommendation technology with applications in the entertainment, healthcare, and productivity sectors. Ultimately, the project aims to improve the way users interact with digital music platforms by providing a truly personalized and intuitive listening experience..

"Music Recommendation System By Facial Expressions", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.n167-n170, April-2025, Available :http://www.jetir.org/papers/JETIR2504D20.pdf

"Music Recommendation System By Facial Expressions", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppn167-n170, April-2025, Available at : http://www.jetir.org/papers/JETIR2504D20.pdf