sindhujagopu/LIP-READING-AI

LIP READING-AI is an AI system that interprets lip movements from video to text in real-time, enhancing communication for the hearing-impaired and deaf, and improving security and interaction in noisy or masked situations. Utilizing advanced deep learning models, it offers pre-trained solutions and customizable tools for various applications.

LIP READING-AI

Welcome to the LIP READING-AI repository! This project focuses on developing an artificial intelligence system capable of reading lips from video inputs. Leveraging state-of-the-art machine learning techniques and deep learning models, our system aims to improve communication accessibility, particularly for the hearing-impaired community.

Features

• Deep Learning Models: Utilizes advanced neural networks for accurate lip reading.
• Video Processing: Efficient video preprocessing and feature extraction.
• Pre-trained Models: Includes pre-trained models for immediate use.
• Custom Training: Provides tools for training models on custom datasets.
• Extensive Documentation: Comprehensive guides and tutorials for setup, usage, and customization.

Getting Started

Prerequisites

• Python 3.7+
• TensorFlow 2.x
• OpenCV
• Other dependencies listed in requirements.txt

Dataset and pre-trained model

• You can download the dataset and the pretrained model from here 👇
• Dataset Link: https://drive.google.com/drive/folders/1zPIXGsSnC7NTh4E40a2QwdpNa-1FRn3A?usp=sharing
• Pre-Trained Model: https://drive.google.com/file/d/1u7ClC7z99SC4X9azEGG4zZhJkpkoYtlY/view?usp=sharing

Installation

Clone the repository and install the required dependencies:

In bash:

• Copy code -> git clone https://github.com/sindhujagopu/LIP-READING-AI.git
• cd LIP-READING-AI
• pip install -r requirements.txt

Model Archietecture(Sample)

Usage

• Facilitates communication in masked situations by focusing on visible lip movements for speech interpretation, helping both the hearing-impaired and deaf.
• Augments surveillance systems by interpreting silent video footage to understand conversations without audio.
• Aids in monitoring sensitive areas by reading lips from video feeds where audio is unclear or unavailable.
• Enhances virtual assistants and customer service systems by incorporating lip-reading capabilities for better user interaction, especially for the deaf.
• Supports language learners and individuals in speech therapy, including deaf people, by demonstrating the formation of words on lips.
• Assists law enforcement in decoding silent video footage to gather crucial evidence from lip movements.
• Improves user experience in media consumption by providing subtitles based on lip reading in noisy environments.
• and a lot more ...

Acknowledgments

We would like to thank the contributors and the open-source community for their valuable work and support.