Song Prediction using Emotional Analysis

This study suggests an integrated method for song prediction that uses computer camera-captured facial expressions to identify emotions in real time. Our method blends facial expression recognition models using Support Vector Machines (SVMs) with song emotion analysis techniques using SVMs with linear kernels, drawing on advances in computer vision and machine learning. SVMs are especially useful in this situation since they work well with limited datasets, which is a typical problem in music emotion analysis and face expression detection. Our system uses these machine learning techniques to correctly determine the user's emotional state (neutral, joy, sadness, surprise, anger, fear, or disgust) and suggests music that is appropriate for their mood (either opposing or matching emotions). In a variety of fields, including therapy and entertainment, this individualized approach improves user experience and engagement. Our technology offers a smooth and user-friendly platform for users to interact with music in accordance with their emotional needs and preferences by combining facial expression detection and music emotion analysis.