Classification of Poetry Text Into the Emotional States Using Deep Learning Technique

The classification of emotional states from poetry or formal text has received less attention by the experts of computational intelligence in recent times as compared to informal textual content like SMS, email, chat, and online user reviews. In this study, an emotional state classification system for text is proposed using the latest and cutting edge technology of Artificial Intelligence, called Deep Learning. For this purpose, an attention-based Bi-LSTM model along with GRU is implemented on the text corpus. The proposed approach classifies the text into different emotional states, like neutral, joy, fear, sadness and anger.

Keywords: Deep learning, emotion recognition, text, attention-based Bi-LSTM, formal text, emotional states