natHACKS 2025 Submission Team: The She-Coders With A He
SignWave is an interactive web-based platform that helps users learn American Sign Language (ASL) through real-time feedback powered by AI and machine learning. Using computer vision, users sign into their webcam and receive instant feedback on accuracy and gesture clarity.
AI-Powered Feedback: Uses pre-trained models to detect and classify hand gestures.
Lessons: Learn the ASL alphabet, numbers, and basic vocabulary.
Mini-Games: Practice with gamified challenges—sign falling prompts, multiplayer sign battles, and more.
Progress Tracking: Automatically saves learning progress for continuous development.
https://docs.google.com/presentation/d/1WiH7RLNqYsvKz_j57tKsCj6MxtciMwE06PnfUDERmio/edit?usp=sharing
Open the website and allow webcam access, and choose a lesson to begin learning ASL. Follow the on-screen prompt and perform hand signs. Use the "Reveal Answer" button if you do not know the sign. Play games with others to test your skill.
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Clone the repository
git clone https://github.com/alexanderho00001/SignWave.git
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Go into the repository
cd SignWave -
Create a virtual environment
python3 -m venv venv
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Activate the virtual environment
source venv/bin/activate -
Go into the backend
cd backend -
Install the backend requirements
pip install -r requirements.txt
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Start the backend server
python3 manage.py runserver
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Open a new terminal window
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Go into the repository again
cd SignWave -
Activate the virtual environment
source venv/bin/activate -
Go into the frontend
cd frontend -
Install frontend dependencies
npm i
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Start the frontend server
npm run dev
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Open the app in your browser Visit → http://localhost:3000
Hand sign references from https://www.lifeprint.com/asl101/pages-layout/fingerspelling.htm Pre-trained AI model for letters from https://huggingface.co/prithivMLmods/Alphabet-Sign-Language-Detection Pre-trained AI model for words from https://github.com/209sontung/sign-language Powered by TensorFlow, MediaPipe, and React
Built during natHACKS 2025