Emotion detection for Bangla language

Abstract

This project aims to identify emotions and generate Bangla-language emojis. Emojis have become essential to digital communication, transcending language borders and improving textual exchanges. This study identifies emotions as Emojis from Bangla text rather than directly detecting them. This study aims to develop a system that uses machine learning and NLP to recognize Bangla text feelings and correlate them to relevant emojis. Using a large sample of Bangla texts, the approach maps emotional content to emojis. Innovative NLP methods, including sentiment analysis, contextual embeddings, and deep learning algorithms, identify emotions in the framework. It’s difficult to effectively read Bengali, a language full of expressions and strong emotions, and produce contextually suitable and culturally informed emojis. An Emotion Detection system for Bangla will improve digital communication in Bangla-speaking populations by making texting more expressive and emotionally resonant. It will advance computational linguistics and human-computer interaction, especially for Bangla. The method integrates smoothly with internet platforms to revolutionize the Bangla-speaking digital exchange of emotions.