Android based Emotion Detection Using Convolutions Neural Networks

With the advent of improved mobile processing capabilities we have seen many novel and useful applications. Among other usecases is the utilization of graphics capabilities of on-board computing capabilities. The study evaluates a new trend of functionality that has been considered in the emotion detection field. The proposed study uses Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to conduct a comparison of which deep learning technique works best for emotion recognition. Both neural network are trained using FER2013 dataset of Kaggle with seven emotion classes. The trained models are evaluated where CNN attains the accuracy of 65% and RNN lack behind with the accuracy of 41%. The trained models are then applied using music player based on one’s facial expressions .The user gets the music according to the mood in two forms. Thus with the application user is provided with new and interactive way of getting the music that provides new and latest music and gets an entertaining music app. The Final Product has great scope as the end product can be modified and expanded where music recommendation can be exchanged with other recommendation systems like news, content etc. according to the emotion fetched.