Deep Learning-Enhanced Emotional Insight: Tailored Music and Book Suggestions Through Facial Expression Recognition

Deep learning has grabed more and more interest in recent year’s in order to the development and implementation of big data. Convolutional neural networks that are deep learning neural networks are crucial for facial picture identification. In this paper, a model recognizes facial expressions and suggests music and recommends book based on related mood is constructed using a mix of automatic music and book recommendation algorithm based on their choices using convolutional neural network for facial recognition technology. This type of suggestion system is authentic and real- time. This research creates a facial expression identification model using FER2013. When implemented on library robots, the facial expression recognition- based book recommendation system can enhance users' experience. The identification of the matching micro expression, the feature of the song is extracted using a history by content for music recommendation algorithm, an innovative approach is then employed to provide the appropriate recommendation. We conclude this paper with the 77% accuracy and recommend suitable music and appropriate book for the users.