Music Recommendation Based on Face Emotion Recognition


  • Madhuri Athavle Department of Computer Engineering, NHITM, Thane, India
  • Deepali Mudale Department of Computer Engineering, NHITM, Thane, India
  • Upasana Shrivastav Department of Computer Engineering, NHITM, Thane, India
  • Megha Gupta Department of Computer Engineering, NHITM, Thane, India



Face Recognition, Feature extraction, Emotion detection, Convolutional Neural Network, Pygame, Tkinter, Music, Player, Camera


We propose a new approach for playing music automatically using facial emotion. Most of the existing approaches involve playing music manually, using wearable computing devices, or classifying based on audio features. Instead, we propose to change the manual sorting and playing. We have used a Convolutional Neural Network for emotion detection. For music recommendations, Pygame & Tkinter are used. Our proposed sys-tem tends to reduce the computational time involved in obtaining the results and the overall cost of the designed system, thereby increasing the system’s overall accuracy. Testing of the system is done on the FER2013 dataset. Facial expressions are captured using an inbuilt camera. Feature extraction is performed on input face images to detect emotions such as happy, angry, sad, surprise, and neutral. Automatically music playlist is generated by identifying the current emotion of the user. It yields better performance in terms of computational time, as compared to the algorithm in the existing literature.


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How to Cite

M. Athavle, D. Mudale, U. Shrivastav, and M. Gupta, “Music Recommendation Based on Face Emotion Recognition”, J. Infor. Electr. Electron. Eng., vol. 2, no. 2, pp. 1–11, Jun. 2021.