Deep learning based Text Emotion Recognition for Chatbot applications
Mounika Karna, D. Sujitha Juliet, R. Catherine Joy
Abstract
Emotions play a vital role in human interaction. We recognize emotion of a person from their speech, face gesture, body language and sign actions. Since humans use many text devices to make interactions these days, emotion extraction from the text has drawn a lot of importance. It is therefore crucial that emotions in textual conversation need to be well understood by the machines, which ultimately provide users with emotional awareness feedback. This paper investigates the effectiveness of deep learning based Long Short-Term Memory mechanism for identification of textual emotions. The study was carried out on `Emotion classification' dataset with six emotional groups. The experimental results proved that LSTM based text emotion classification provides relatively higher accuracy compared to the existing learning methods.