signlanguagerecognition

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

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.

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

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.

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.

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

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 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.

Bachelor Thesis at the Wroclaw University of Science and Technology.

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.

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.

手语翻译动作捕捉手套Alpha版本EchoGlove-Hall-IMU-3D hand animation rendering and bidirectional sign language translation

American Sign Language Recognition

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

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.

A Real-Time Sign Language Recognition System that uses computer vision and machine learning to detect and classify hand gestures through a webcam. The system tracks hand movements, processes images, and recognizes multiple sign language gestures, enabling faster and more accessible communication between hearing-impaired and non-sign-language users.