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American Sign Language (ASL) translator built with deep learning + computer vision. Converts real-time hand gestures to text using a CNN trained on 80K+ labeled images (~95%+ accuracy). Features a Flask + React web app, AWS deployment, and an interactive UI for live translation.

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SignSync

AI-Powered American Sign Language (ASL) Translator

SignSync is an AI-driven ASL-to-text web application that bridges the communication gap between the Deaf and hearing communities.
Built using deep learning and modern web technologies, it recognizes real-time ASL gestures and translates them into English text through an accessible, responsive interface.


Features

  • Real-Time Translation: Converts ASL hand gestures to English text using a trained Convolutional Neural Network (CNN).
  • High Accuracy: Model trained on 80K+ labeled ASL images with over 95% recognition accuracy.
  • Accessible Design: Clean, modern UI built with React + TailwindCSS for seamless interaction.
  • Scalable Backend: Flask API deployed on AWS, integrating TensorFlow model inference and REST endpoints.
  • Cross-Device Support: Works smoothly across desktop and mobile browsers.

Tech Stack

Frontend: React, TailwindCSS
Backend: Flask (Python), TensorFlow, scikit-learn
Deployment: AWS EC2, S3
Languages: Python, JavaScript, HTML, CSS
Version Control: Git + GitHub


Model Overview

The AI model leverages transfer learning with architectures such as ResNet50, VGG16, and InceptionV3 to balance real-time inference speed and accuracy.
It was trained on a custom dataset of over 80,000 ASL gesture images, processed with OpenCV and NumPy.
Evaluation achieved a validation accuracy of 95%+ with strong generalization across lighting and background conditions.


Setup Instructions for Local Device

Prerequisites

  • Python 3.8+
  • Node.js 16+
  • npm or yarn
  • TensorFlow and Flask installed locally

About

American Sign Language (ASL) translator built with deep learning + computer vision. Converts real-time hand gestures to text using a CNN trained on 80K+ labeled images (~95%+ accuracy). Features a Flask + React web app, AWS deployment, and an interactive UI for live translation.

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