FACIAL EMOTION RECOGNITION FOR EMOJI RECOMMENDATION IN CHAT APPLICATION

Abstract

his thesis presents a different way to deal with improving the client experience in chat applications by coordinating emotion recognition. The point is to empower constant recognition of the client's emotion during the conversation and give ideas of stickers or emoticons as needs be. The chat app can accurately analyze the user's emotional state based on facial expressions captured by the device's camera by utilizing facial emotion recognition algorithms. Users can easily and interactively express their feelings in digital conversations with the proposed system. To accurately recognize emotions, the research aims to create a robust and effective framework that combines real-time image processing with deep learning methods. Additionally, the thesis explores the design and implementation of an intelligent recommendation system that suggests relevant stickers or emojis based on the detected emotions. A definitive objective is to make a connecting with and expressive correspondence stage that upgrades client experience and works with more meaningful interactions