Abstract:

Music is an integral part of our lives, and with the advancement of technology, music players have become more sophisticated. However, finding the right song to match our current emotional state or physical gesture can be a tedious task. Current methods for creating automated playlists are often inefficient and may require additional equipment like sensors or EEG.To address this issue, we propose a novel approach that utilizes real-time face expression and gesture extraction to create personalized playlists. Unlike existing methods that rely on speech processing or require extensive computing power, our approach is both cost-effective and efficient

Description:

Convolutional neural network, Deep Learning, Streamlit Application