Popular GitHub Repositories for Sign Language Recognition

This repo contains the official code of our work SAM-SLR which won the CVPR 2021 Challenge on Large Scale Signer Independent Isolated Sign Language Recognition.

I created an application which takes in live speech or audio recording as input, converts it into text and displays the relevant Indian Sign Language images or GIFs, using Natural Language Processing and Machine Learning Algorithm.

Repository accompanying the "Sign Pose-based Transformer for Word-level Sign Language Recognition" paper

SAM-SLR-v2 is an improved version of SAM-SLR for sign language recognition.

A CNN based human computer interface for American Sign Language recognition for hearing-impaired individuals

A video call apps to enable deaf people to communicate with normal people using sign language recognition and speech-to-text

communication application to make Complete conversation with deaf people

This is a Streamlit app that detects, classifies, and translates Indian Sign Language (ISL) using custom-trained YOLOv8 and Vision Transformer (ViT) models. It supports real-time image capture, multi-language text translation, and text-to-speech conversion, enhancing accessibility and communication for ISL users.

Hierarchical Windowed Graph Attention Network for Sign Language Recognition

Indian Sign language Recognition using OpenCV

This is an simple implementation of MobileNet for sign language digit prediction.

A web app that converts sign language to audio output using speech synthesis.

Alphabet-Sign-Language-Detection is an image classification vision-language encoder model fine-tuned from google/siglip2-base-patch16-224 for a single-label classification task. It is designed to classify images into sign language alphabet categories using the SiglipForImageClassification architecture.

Pose-based word-level sign language recognition with BERT-styled transformer in Keras

This repository contains the implementation of a real-time gesture recognition system using Mediapipe for keypoint extraction and a Bidirectional LSTM neural network for gesture classification. The system captures video input, processes it to detect and track facial, pose, and hand landmarks, and predicts gestures based on the extracted keypoints.