A Novice Approach to Efficient Lip Reading

In an interconnected world, effective communication is crucial, especially for individuals with hearing impairments relying on lipreading. Artificial Intelligence and Machine Learning have revolutionized the traditional two-step process of manually ensuring clear lip visibility and understanding spoken words. This paper delves into the cutting-edge LipNet, the inaugural sentence-level lipreading model designed for end-to-end processing. In contrast to earlier models confined to word classification, LipNet achieves an impressive 95.2% accuracy in predicting sentences at the GRID corpus level. This achievement exceeds the performance of human lipreaders and surpasses the previous state-of-the-art word-level accuracy of 86.4%, marking a substantial advancement in lipreading technology.