Face Emotion Based Music Recommendation System Using Modified Convolution Neural Network

• Published in: 2023 International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE) pp. 1 - 6
• Main Authors: Mabel Rani, A Jaya, S, M.Nivetha, Jothi Swaroopan, N M, Hari Kumar, K
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2023
• Subjects: Convolution; Data Security; Deep Learning; Face Emotion; Face recognition; Modified Convolution neural network; Mood; Music; Music Recommendation; Neural networks; Real-time systems; User experience
• DOI: 10.1109/RMKMATE59243.2023.10368948

In this paper, proposed a new vision to personify music recommendation by face emotion recognition technology. Emotions play a crucial role in the way humans perceive and respond to music. This system aims to enhance the user experience by recommending music based on their real-time facial expressions, allowing for a more immersive and emotionally resonant listening experience. So here employed deep learning techniques to detect facial emotions accurately and use them as input to our music recommendation algorithm. The proposed method modified convolution neural network ensures user privacy and data security by processing emotions locally on the user's device without uploading any sensitive information to external servers. Through experimental evaluation, here demonstrate the effectiveness and usability of the emotion-based music recommendation system and finally shown this method is very effective with the help of accuracy and F1 score.