LipChat is a lipreading application that decodes text from the movement of a speaker's mouth. It is a remake of the LipNet model, designed for end-to-end sentence-level lipreading.

• Converts a sequence of video frames to text
• Uses spatiotemporal convolutions, a recurrent network, and connectionist temporal classification loss
• Trained entirely end-to-end
• Achieves high accuracy in converting speech from videos to text(95.2%)

1. Clone the repository:

   git clone https://github.com/abuzar0013/First-Minor-Project.git

2. First, create a Conda environment to easily manage all the required libraries.

   conda create --name LipChat 

   Activate LipChat environment

   conda activate LipChat

3. Install dependencies:

   pip install -r requirements.txt

To run this app, please adjust all the file paths according to your system.

1. Run the LipChat app:

   python streamlitpp.py

   OR

   streamlit run /FIRST-MINOR-PROJECT/app/streamlitapp.py

2. Follow the on-screen instructions to input video files for lipreading.

Contributions are welcome! Please fork the repository and submit a pull request with your changes.

This project is licensed under the MIT License - see the LICENSE file for details.

• Wand et al., 2016; Chung & Zisserman, 2016a for pioneering work in end-to-end lipreading
• Gergen et al., 2016 for their word-level state-of-the-art accuracy
• Easton & Basala, 1982 for studies on human lipreading performance