Signapse is an open source software tool for helping everyday people learn sign language for free!

Using yolo-v8 to train on custom dataset for sign language recognition

A real-time American Sign Language (ASL) recognition system

Sign Language Recognition System is an AI-powered application that enables real-time sign language recognition using MediaPipe and an MLP model. It captures hand gestures, extracts landmark features, and predicts sign language letters dynamically. The project also explores MobileNetV2 and aims to expand into Text-to-Sign Language generation.

Signfy is a Video Chat app that incorporates sign language translation to bridge the communication gap between the deaf and hearing communities.

Sign language gesture recognition is done in two ways. Alphabets are detected from sign language and words are formed using this. The words thus formed is then converted to speech. Another method includes recognizing gestures which include words.

Awesome-Sign-Language-Processing-SLP The most comprehensive, up-to-date collection of Sign-Language Processing resources on the internet.

This program will use gesture detection to help identify common ASL gestures as well as alphabets, translating them into sentences.

it able to detect ten type USA sign language. which is Okay, Peace, Thumbs up, Thumbs down, Call me, Stop, I Love You, Hello, No, Smile.

Applied SSD integrated with MobileNet model for object (sign gestures) detection and recognition and the model is trained using Transfer Learning, with the aim to develop a web app for real-time ASL recognition from user input & then to generate text in English.

Bachelor Thesis at the Wroclaw University of Science and Technology.

Practical, end-to-end notebooks and examples that teach the pose-format library from basics to advanced workflows (conversion, Normalizing Data,Interpolation visualization, augmentation).

This web-based app detects and interprets sign languages into English words in real-time in order to help speech-impaired individuals communicate with others more easily.

American Sign Language Recognition

This is a model to classify Vietnamese sign language using Motion history image (MHI) algorithm and CNN.

This project is aimed at detecting American Sign Language (ASL) alphabets in real-time using computer vision. The system utilizes OpenCV for image processing, MediaPipe for hand detection, and a Random Forest classifier from scikit-learn for alphabet recognition.

Aplicación que permite traducir lengua de señas a audio y texto.

A 2D platformer that teaches American Sign Language (ASL) using Leap Motion-powered hand gestures

This project involves creating a real-time sign language detection system using CNNs to translate sign language gestures into text. It aims to improve communication accessibility for the hearing-impaired by accurately recognizing and displaying sign language gestures from live video input in real-time.