• Rahul Raut
• Aditya Dumbare
• Harshal Shinde
• Rudrapratap Sharma
• Nakul Dingar

Human facial expression recognition is one of the foremost powerful and difficult tasks in social communication yet plays very important role in communicating the emotions and intensions of human beings. Generally, facial expressions are the most unique and natural way of non-verbal communication with emotions. Along with communication we love listening music according to the mood we’re in for the moment. For this reason there have been some advancements in technology that integrate emotional intelligence into existing machine learning applications are being studied. This paper is a survey on facial expression recognition (FER) and music classification techniques that embody the 3 major stages like preprocessing, feature extraction and classification. This survey explains the varied kinds of FER and music classification techniques with its major contributions. The performance of varied FER techniques is compared supported to the amount of expressions recognized and complexness of algorithms. Databases like JAFFE, CK, and a few different kind of face expression databases are mentioned during this survey.

Machine Learning, SVM, Random Forest, Classifier,, K-means, Matplotelib, sk-learn, pandas, wine quality, data analysis

"Review Paper on Music Genre Classification and Play Songs Using Facial Emotion", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.h575-h580, May-2022, Available :http://www.jetir.org/papers/JETIR2205876.pdf

"Review Paper on Music Genre Classification and Play Songs Using Facial Emotion", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. pph575-h580, May-2022, Available at : http://www.jetir.org/papers/JETIR2205876.pdf