Sign-Language-To-Text-Conversion and ASL-Recognition-System

Sign-Language-To-Text-Conversion
53
Established
ASL-Recognition-System
24
Experimental
Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 6/25
Adoption 3/25
Maturity 15/25
Community 0/25
Stars: 348
Forks: 127
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 3
Forks: —
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
No Package No Dependents

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.

sign-language communication-aid deaf-and-mute-support human-computer-interaction

About ASL-Recognition-System

Muhib-Mehdi/ASL-Recognition-System

The ASL Recognition System is a real‑time American Sign Language (ASL) gesture‑recognition application built with Python, TensorFlow Lite, OpenCV, and MediaPipe. It captures hand landmarks from a webcam, processes them through a lightweight neural network, and instantly translates the gestures into alphabet letters (A‑Z).

Related comparisons

Sign-Language-To-Text-Conversion and Sign-Language-To-Text-and-Speech-Conversion Sign-Language-To-Text-Conversion and Sign-Language-to-Speech

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