Real-Time Hand Gesture Recognition with Voice Conversion for Deaf and Dumb

Individuals primarily communicate with one another through various means, such as verbal language, written language, or nonverbal cues. However, for those who are deaf and dumb, the only mode of communication is sign language. Unfortunately, communication becomes difficult if such people are unaware of sign language, leading to frustration and a lack of ability to express emotions effectively. In emergency situations, the inability to communicate effectively can be particularly challenging. Researchers have looked exploring ways to translate hand motions into text and sounds in order to find a solution around this problem. Both vision-based and non-vision-based methods are frequently employed to identify hand motions or gestures. The former uses sensors, while the latter uses cameras for gesture detection. This study focuses on a vision-based approach and develops a gesture recognition system using artificial neural networks. The system locates and recognizes hand movements, allowing for communication to be maintained with others. The benefits and drawbacks of hand movement recognition are also examined. Overall, this research aims to address the communication barriers faced by those who rely on sign language and to improve their ability to communicate effectively in emergency situations.