ECGText: Crafting Emotional Texts through GenAI

The generation of emotionally nuanced text is a growing area of interest in AI, particularly in enhancing human-machine interaction. This paper presents ECGText (Emotionally Cognizant Generation of Text), a novel model that integrates emotional intelligence into GPT-based text generation. The motivation behind this study stems from the limitations of current text generation models, which lack the ability to generate emotionally resonant content. By incorporating sentiment analysis and emotion recognition into the text generation process, ECGText produces emotionally appropriate outputs, enhancing engagement and relatability. Through comprehensive experiments and evaluations using diverse datasets, results demonstrate that ECGText outperforms baseline models in generating sentiment-rich text while maintaining coherence and fluency. This study advances the field of AI-driven communication, bridging the gap between machine-generated text and human emotional expression.