• Shubham Bobade
• Pratik bhusari
• amruta dhagude
• swapnil dhumal

The human face is an important instrument for determining someone's emotional state. The required input is instantly obtained from the subject's face using a camera. One way to use this input would be to extract the data and use it to infer someone's mood. The list of songs that fit the "mood" that was established from the previously supplied input may then be obtained using this data. This information can then be used to acquire the list of songs that match the "mood" and removes the laborious and time-consuming chore of manually sorting music into distinct lists. To detect emotions, we have employed a convolutional neural network. We use an integrated camera to record facial expressions. Using input facial photos, feature extraction is used to identify emotions including surprise, happy, angry, sad, and neutral. By figuring out the user's current emotional state, a playlist of music is automatically constructed. Compared to the approach in the current literature, it produces better results in terms of computational time. By using facial expression analysis, the Music Recommendation System seeks to provide a more personalized and engaging music discovery experience by gaining a deeper knowledge of the user's emotions. This novel combination of computer vision and music recommendation algorithms has the potential to completely change how people engage with and find music by dynamically and responsively responding to their emotional states.

"Music Recommendation System Using Facial Expression ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.f126-f134, November-2023, Available :http://www.jetir.org/papers/JETIR2311513.pdf

"Music Recommendation System Using Facial Expression ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppf126-f134, November-2023, Available at : http://www.jetir.org/papers/JETIR2311513.pdf