Welcome to the Sign-Language-Glove project! This innovative hardware-based solution translates American Sign Language (ASL) gestures into text or speech in real-time. Leveraging the power of Arduino Uno, flex sensors, and ADXL335 accelerometers, the Sign-Language Glove aims to bridge the communication gap between the deaf and hearing communities.
- Real-Time Translation: Converts ASL gestures into text and speech instantly.
- Wireless Connectivity: Uses Bluetooth for seamless connection to mobile devices and computers.
- User-Friendly Interface: Mobile app and desktop software for easy interaction and customization.
- Extensive Vocabulary: Supports a wide range of ASL gestures with the ability to add custom signs.
- Data Logging: Records gesture data for analysis and improvement.
- Arduino Uno: Central microcontroller for data processing.
- Flex Sensors: Detect finger movements.
- ADXL335 Accelerometer: Tracks hand orientation and motion.
- Bluetooth Module: For wireless communication with mobile devices and computers.
- Programming Languages: C/C++ for Arduino, Python for data processing.
- Machine Learning: TensorFlow or PyTorch for gesture recognition.
- Mobile App: React Native for cross-platform compatibility.
- Desktop App: Electron.js for a unified experience across OS.
- Attach the flex sensors to each finger of the glove.
- Connect the ADXL335 accelerometer to the Arduino Uno.
- Pair the Arduino Uno with a Bluetooth module.
- Upload the firmware to the Arduino Uno using the Arduino IDE.
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Clone this repository:
git clone https://github.com/Slygriyrsk/Sign-Language-Glove.git
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Navigate to the project directory:
cd Sign-Language-Glove -
Install the required dependencies:
pip install -r requirements.txt
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Run the gesture recognition script:
python gesture_recognition.py
The mobile application provides an interface for users to interact with the device, including features for converting sign language to audio or video signs.
Establish a connection between your phone and the glove by selecting the appropriate Bluetooth address.
This is done using MIT App Inventor: MIT App Inventor
Here are some basic readings from our records:
- Wear the glove and ensure all sensors are securely attached.
- Turn on the Arduino Uno and pair it with your mobile device or computer via Bluetooth.
- Open the mobile or desktop app.
- Perform ASL gestures; the corresponding text and speech output will be displayed and played in real-time.
Contributions are always welcome! Please see contributing.md for ways to get started.
Please adhere to this project's code of conduct.
- Report Bugs: Use the Issues section to report any bugs or feature requests.
- Fix Issues: Fork the repository, make your changes, and submit a pull request.
- Improve Documentation: Help us improve the project's documentation by adding tutorials, examples, and clarifications.
- @Slygriyrsk
- @maheshkatyayan
This project would not have been possible without the dedicated efforts and contributions of our amazing team members:
- Saharsh Kumar: Team Leader, developed the Bluetooth communication application, ensuring seamless connectivity between the glove and mobile devices.
- Hitesh Kumar: Focused on hardware integration and wrote the core code for the Arduino Uno, flex sensors, and ADXL335 accelerometers.
- Mahesh K Katyayan: Worked on the signal processing and machine learning aspects, laying the groundwork for future innovations in gesture recognition.
Thank you for your hard work and commitment to making this project a success! 🎉
