Creation of A Music Recommendation System using Facial Expression Recognition with MATLAB
Keywords:
Facial expression, Haar cascade technique, Music identification, CNNAbstract
Choosing music from a wide array of options often poses a challenge for individuals. Various recommendation frameworks have been made available for themes such as music, food, and shopping, depending on the user's perspective. The main objective of our music recommendation system is to provide consumers with suggestions that align with their preferences. Examining the user's emotions and facial expressions might provide insights on their present emotional or mental state. The domains of music and video provide enough opportunities to provide customers with a diverse range of choices based on their preferences and stored information. Humans commonly transmit their intentions and the context of what they say through their facial expressions. More than 60% of users feel that their music library occasionally contains too many songs, making it challenging to decide which one to play. It could assist someone in selecting the music they ought to listen to by developing a recommendation system, enabling them to feel less bothered all around. After identifying the most suitable track that aligns with the user's mood, songs are shown to the user based on their mood, eliminating the need for the user to manually search or look for music. The user's picture is obtained via the use of a camera. The user is thereafter recorded on camera as a song from their playlist that most accurately reflects their mood or attitude is played.
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