Lip Reading decodes speech by interpreting visual cues from lip movements. This technique is valuable in noisy environments and provides accessibility support for individuals with hearing impairments. Deep learning models, such as convolutional neural networks (CNNs), are trained on audio-visual datasets to map lip movements to corresponding phonemes. Lip reading presents challenges, including variations in speaker accents, co-articulation effects, and the similarity of visually identical phonemes. Applications include assistive technology, security systems, and enhancing ASR performance in difficult acoustic conditions. Research focuses on integrating lip reading with speech models for improved performance and exploring real-time lip reading capabilities.

TODO: please update test set description