Interactive Communication System for Deaf and Mute Individuals Using Gesture and Speech Recognition

Deaf and mute individuals often face challenges in communicating with others who are unfamiliar with sign language. This paper proposes a two-way communication system that bridges this gap by converting sign language gestures into text and speech and vice versa. The system uses a vision-based gesture recognition approach for translating hand movements into corresponding text and voice outputs. Additionally, spoken or typed text is converted into visual or haptic feedback to facilitate two-way interaction. The methodology employs advanced image processing algorithms, Support Vector Machines (SVM) for classification, and text-to-speech (TTS) and speech-to-text (STT) systems for seamless communication. Experimental results demonstrate a recognition accuracy of over 95% for common signs, making the system effective and reliable.