Gestura

Gestura – Transforming Gestures into Meaning. ✨

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Gestura – Bridging Signs to Speech

Inspiration

Communication barriers between the Deaf and Hard-of-Hearing (DHH) community and non-sign language users inspired us to create Gestura. Sign language is a rich and expressive form of communication, yet many struggle to understand it. Our goal was to develop a system that could translate sign language into text and speech in real-time, making communication more accessible and inclusive.

What It Does

Gestura uses computer vision and AI to detect hand gestures and translate them into meaningful text or speech. The system:

  • Captures hand movements through a camera.
  • Recognizes sign language gestures using a trained AI model.
  • Converts gestures into real-time text and audio output for seamless communication.
  • Provides a user-friendly interface that enables anyone to interact with sign language users effortlessly.
  • Stores translations on a blockchain with a timestamp for security, transparency, and authenticity.

How We Built It

We followed a structured approach to develop Gestura:

  1. Data Collection & Preprocessing

    • Collected and labeled a dataset of sign language gestures.
    • Used OpenCV and MediaPipe for hand tracking and feature extraction.

  2. AI Model Development

    • Trained a Convolutional Neural Network (CNN) using TensorFlow/Keras.
    • Optimized the model for real-time gesture recognition with high accuracy.

  3. Backend Implementation

    • Built a Flask API to process video input and return gesture predictions.
    • Implemented WebSockets for real-time communication.
    • Integrated blockchain technology to store translations securely with a timestamp.

  4. Frontend Development

    • Developed a React-based UI for users to interact with the system.
    • Integrated Text-to-Speech (TTS) APIs to convert recognized gestures into audio.

Challenges We Ran Into

  • Real-Time Processing – Optimizing the AI model to run smoothly without delays.
  • Gesture Variability – Accounting for different hand shapes, angles, and lighting conditions.
  • Dataset Limitations – Expanding our dataset to include more sign language gestures.
  • Speech Accuracy – Ensuring the text-to-speech conversion sounds natural and precise.
  • Blockchain Storage – Efficiently storing translations on a blockchain while maintaining performance.

Accomplishments That We're Proud Of

  • Successfully trained and deployed a real-time sign language recognition model.
  • Built an accessible and intuitive React frontend for seamless user interaction.
  • Optimized gesture detection accuracy for different users and environments.
  • Implemented secure blockchain-based translation storage, ensuring authenticity and preventing tampering.
  • Created a system that could potentially improve accessibility for millions of people.

What We Learned

  • Hands-on experience with computer vision, AI model training, and real-time processing.
  • The importance of inclusive design and accessibility in technology.
  • Optimizing deep learning models for better speed and accuracy.
  • Overcoming real-world challenges in gesture recognition and language translation.
  • Integrating blockchain for decentralized, secure, and tamper-proof translation storage.

What's Next for Gestura

We plan to enhance Gestura by:

  • Expanding the gesture dataset to include more sign languages and variations.
  • Improving model accuracy using advanced deep learning techniques.
  • Integrating voice input to make the system bidirectional.
  • Developing a mobile application for on-the-go sign language detection.
  • Exploring AR/VR integration to create an immersive sign language learning experience.
  • Enhancing blockchain implementation by allowing verified users to access stored translations for further analysis and research.

🚀 Gestura – Empowering Communication, One Gesture at a Time! 🤟

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