Gesture and Emotion Detection using Quantum Computing for Enhanced Recognition and Analysis

The research on “Gesture and Emotion Detection using Quantum Computing” is driven by an increasing need to overcome the linguistic and emotional barriers encountered by the Deaf community. With a deep understanding of the complexity of American Sign Language (ASL), this research bridges the communication gap by seamlessly translating ASL into speech, thereby increasing the accessibility for a wider audience. Going beyond mere translation, this research study aims to integrate the converted speech with the emotional expressions inherent in sign language. The proposed research idea stems from the recognition that existing communication technologies often overlook the rich emotional content conveyed through ASL. By integrating facial emotion identification, this research study aims to capture a diverse range of emotions embedded in sign language communication. This dual approach not only increases human understanding but also enhances the inclusivity in linguistic and emotional experiences for both Deaf and hearing communities. Ultimately, the objective of this research study is to develop a comprehensive system capable of accurately recognizing ASL, transforming it into articulate speech, and simultaneously conveying the emotional depth inherent in sign language expression. Through this research study, the emotion-enhanced sign language to speech conversion research seeks to redefine the communication accessibility, enabling a more interconnected and empathetic society.