Signease is a user-friendly desktop application that brings together multiple American Sign Language (ASL) translation tools into a single interface.

1. Sign Language to Audio Translator
   Uses hand gesture recognition from a webcam to detect ASL letters and speak them aloud.

2. YouTube to ASL Interpreter
   Fetches captions from YouTube videos and displays corresponding ASL letter animations using pre-stored sign videos.

3. Audio to ASL Translator
   Listens to audio from the microphone and displays matching ASL signs as videos.

• Requires Python 3.7 or higher
  (Recommended: Python 3.10+ for best package support)

Install all dependencies using:

pip install -r requirements.txt

Or manually install them:

pip install tk opencv-python cvzone numpy mediapipe pyttsx3 SpeechRecognition youtube-transcript-api pillow

tk
opencv-python
cvzone
numpy
mediapipe
pyttsx3
SpeechRecognition
youtube-transcript-api
pillow

signease/
│
├── main.py                  # GUI launcher
├── prediction1.py           # Camera-based sign detection
├── ytasl2.py                # YouTube video to ASL
├── AudioToASL.py            # Audio to ASL translator
├── M/
│   ├── keras_model.h5       # Trained sign language model
│   └── labels.txt           # Labels used in classification
├── gifs/
│   ├── A.mp4, B.mp4, ...    # ASL sign videos for each letter
├── requirements.txt
└── README.md

Launch the hub interface:

python main.py

Then select one of the translator tools from the GUI.

• Ensure your webcam and microphone are properly connected.
• Store ASL sign videos for each alphabet as A.mp4, B.mp4, ... inside a folder named gifs/.
• Trained model and label files should be inside the M/ directory.

• Add support for full-word translation.
• Use deep learning models for improved accuracy.
• Add support for real-time ASL feedback overlay on videos.

This project is open source under the MIT License.