Music Recommendation using CNN

@article{1703845,
      author = {Mohammed Basim K, Adarsh D, Faiz Mohammad Dangar},
      title = {Music Recommendation using CNN},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {6},
      number = {4},
      pages = {40-44},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1703845.pdf},
      abstract = {A user's choice of music is influenced by their mood as well as their past musical tastes and musical substance. In this study, we introduce a powerful music recommendation system that makes music suggestions depending on the user's current mood. It primarily focuses on the Convolutional Neural Network (CNN) model, which distinguishes seven different facial expressions in humans using Mobile Net architecture. Three modules make up our system: the Recommendation Module, the Music Classification Module, and the Emotion Module. The Emotion Module uses CNN to determine the user's current mood after receiving a picture of their face as input. The Music Classification Module uses auditory attributes to classify music and achieves a phenomenal result of 98% songs into 4 categories of mood.},
      keywords = {Convolutional Neural Network; Emotion Module; Music Classification Module; the Recommendation Module;},
      month = {October},
  }