• Tarush Wagh
• Shruti Naik
• Parth Shinde
• Neha Shivarkar
• Suhas Rathod

When predicting a person's emotions and mood, the face is crucial. Typically, a camera is used to extract human emotions. Numerous applications are being created based on the recognition of human emotions. A few examples of applications for emotion detection include business notification recommendation, e-learning, the diagnosis of mental illness and depression, and criminal activity. We create a prototype for a dynamic music recommendation system based on human emotions in this system that is being suggested. Songs for each emotion are taught based on human listening patterns. The emotion on a real person's face is recognized using an integration of feature extraction and machine learning techniques. Once the mood is determined from the input image, the appropriate music will be played to keep the users' attention. With this method, the application connects with user emotions and gives them a personal touch. In order to create music players that are emotion-based, our technology is focused on understanding human emotions using computer vision and machine learning approaches. We use CNN model architecture for music recommendation and emotion recognition in our experiments.

Image processing, CNN, Music recommendation, Emotion detection, Python, Music player

"Smart Emotion Based Music Player Using Python Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.f337-f346, May-2023, Available :http://www.jetir.org/papers/JETIR2305549.pdf

"Smart Emotion Based Music Player Using Python Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppf337-f346, May-2023, Available at : http://www.jetir.org/papers/JETIR2305549.pdf