Sign-Language-To-Text-Conversion and Sign-Language-to-Speech
About Sign-Language-To-Text-Conversion
emnikhil/Sign-Language-To-Text-Conversion
Sign Language to Text Conversion is a real-time system that uses a camera to capture hand gestures and translates them into text, words, and sentences using Computer Vision and Machine Learning.
This project offers a real-time system that translates American Sign Language (ASL) fingerspelling into written text. By using a standard camera, it captures hand gestures and converts them into individual letters, which can then be combined to form words and sentences. It is designed for individuals who need to communicate with Deaf and Mute people who primarily use sign language.
About Sign-Language-to-Speech
RhythmusByte/Sign-Language-to-Speech
Real-time ASL interpreter using OpenCV and TensorFlow/Keras for hand gesture recognition. Features custom hand tracking, image preprocessing, and gesture classification to translate American Sign Language into text and speech output. Built with accessibility in mind.
This tool helps bridge communication gaps by translating American Sign Language (ASL) hand gestures into spoken words and text in real-time. It takes live video of a person signing and converts their hand movements into understandable output. Anyone interacting with deaf or hard-of-hearing individuals, such as educators, customer service professionals, or family members, could use this to facilitate smoother conversations.
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