Event based Sign-Language-Translation
Python library & framework to build custom translators for the hearing-impaired and translate between Sign Language & Text using Artificial Intelligence.
Effortless Real-Time Sign Language Translation
ASL Translation Kotlin/Flutter application with custom task file.
Resources about Sign Language Processing (e.g., Sign Language Recognition / Translation / Production)
✌️ ASL ⭤ English Translation with MediaPipe, PointNet, ThreeJS and Embeddings
The Sign Language Interpreter leverages Mediapipe and a hybrid Convolutional Neural Network (CNN) to translate sign language gestures into text. This project is designed to help people who communicate using sign language interact more seamlessly with those who do not understand it.
Paper list of sign language, including sign language recognition(SLR), sign language translation(SLT) and other interesting work. Quick start your awesome work with us!! 🤟🤟🤟
Sign language recognition
Bu uygulama, işitme engelli bireylerin sesli veya yazılı ifadeleri işaret dilinde video olarak görmelerini sağlayan bir mobil uygulamadır. Bu sayede, işitme engelli bireyler bulundukları ortamlarda konuşulanları anlayabilir ve sohbete katılabilirler.
Neural Network that is able to translate any sign language into text.
Academic R&D project: Sign-Polish Language Video Translator
a browser extension that converts auto-generated YouTube subtitles into real-time sign language!
A comprehensive table of word-level video sign language datasets
Sign Language Detection & Translation Web App
Traductor de Lengua de Señas Boliviana (LSB) a texto utilizando redes neuronales con mecanismos de atención.
A real-time sign language gesture interpretation using deep learning and pose estimation, supported by an LSTM neural network architecture.
World Level American Sign Language Recognition and Translation to Spoken Language
Sign Language Translator enables the hearing impaired user to communicate efficiently in sign language, and the application will translate the same into text/speech. The user has to train the model, by recording its own sign language gestures. Internally it uses MobileNet and KNN classifier to classify the gestures.
This project aims to develop a cutting-edge system that detects sign language from images and converts it into audio, and vice versa.
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