Lip-Reading Project

This project uses deep learning techniques to understand and transcribe sentences by analyzing lip movements without any accompanying sound. It leverages a vocabulary of characters to decode the lip movements into textual representation.

Table of Contents

• Overview
• Features
• Requirements
• Installation
• Usage
• Model Architecture
• Results
• Future Work

Overview

Lip reading, also known as speech reading, involves understanding spoken words by visually interpreting the movements of the lips, face, and tongue. This project aims to provide a deep learning solution for lip reading, enabling the transcription of silent videos into text.

Features

• Character-Based Vocabulary: Uses a set of characters including alphabets, punctuation, and numbers.
• Deep Learning Model: Utilizes Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks for feature extraction and sequence modeling.
• TensorFlow Implementation: Built using TensorFlow and Keras, providing easy integration and deployment.

Requirements

• Python 3.6 or higher
• TensorFlow 2.x
• NumPy
• OpenCV