Open AccessFace Detection Based Emotion Recognition Using Deep Learning
Author(s) -
Suraj Rathrod,
Akshay Patil,
Rohan Satpute,
Prof. Komal Jadhav
Publication year - 2022
Publication title -
international journal of advanced research in science, communication and technology
Language(s) - English
Resource type - Journals
ISSN - 2581-9429
DOI - 10.48175/ijarsct-3333
Subject(s) - feeling , facial expression , mood , face (sociological concept) , nonverbal communication , emotion detection , computer science , psychology , emotion recognition , cognitive psychology , speech recognition , social psychology , artificial intelligence , communication , linguistics , philosophy
Music aids in the reduction of stress, the development of self-esteem, and the improvement of health, among other things. It can be broken down into a number of different genres. People tend to choose a particular music genre based on their mood and interests. As a result, there is a clear need for a platform that can automatically recommend music based on an individual's feelings. Facial expressions can be seen of as a type of nonverbal communication that can transmit information about a person's moods. As a result, Egophony is primarily concerned with the development of an application that would recommend songs to the end user based on their emotions and interests by capturing their facial expressions. We've developed a system that can recognize emotions based on facial expressions. Once the mood has been identified, the system will recommend a playlist of music from a specific genre based on the emotion. It will ultimately save a significant amount of time that would otherwise be spent manually searching, selecting, and playing songs.