TEXT2EMOTIONS: A Web Application for Emotion Visualization in Children’s Tales

In the contemporary era, accessing a vast repository of information through the internet has reshaped education. Filtering this wealth of knowledge for specific learning needs, especially for young children, remains a challenge. This research project addresses this challenge by exploring emotional nuances in English stories, employing advanced technologies like Natural Language Processing (NLP) and Machine Learning (ML). Comparing various models, including artificial neural networks, LSTM, GRU, and BiLSTM, the study identifies LSTM as the most accurate in discerning emotions. The project culminates in a web application that translates emotional information into visually comprehensible images, aiding parents and educators in selecting age-appropriate stories for children's emotional development.