Visual Voice: An AI Powered Lip Reading Technology

By examining lip movements, lipreading, known as visual speech recognition, attempts to understand language that is spoken. This technique improves speech recognition systems and provides substantial advantages for those people who have hard time hearing. By using diverse and preprocessed data from datasets like GRID, this study aims to overcome these problems and enhance model performance. In order to improve comprehension of speech sequences and make sure the model better represents the flow of spoken words, temporal context integration is used. In order to extract features, the suggested lipreading model integrates several deep learning approaches, such as the CNN and BiLSTM networks. The model's effectiveness was demonstrated by its 97.6 % accuracy on the GRID dataset. This development could help people with hearing loss and enhance speech recognition software.