The Lip Reading in the Wild (LRW) dataset a large-scale audio-visual database that contains 500 different words from over 1,000 speakers. Each utterance has 29 frames, whose boundary is centered around the target word. The database is divided into training, validation and test sets. The training set contains at least 800 utterances for each class while the validation and test sets contain 50 utterances. Source: Towards Pose-invariant Lip-Reading Image Source: https://www.robots.ox.ac.uk/~vgg/data/lip_reading/lrw1.html
The Oxford-BBC Lip Reading Sentences 2 (LRS2) dataset is one of the largest publicly available datasets for lip reading sentences in-the-wild. The database consists of mainly news and talk shows from BBC programs. Each sentence is up to 100 characters in length. The training, validation and test sets are divided according to broadcast date. It is a challenging set since it contains thousands of speakers without speaker labels and large variation in head pose. The pre-training set contains 96,318 utterances, the training set contains 45,839 utterances, the validation set contains 1,082 utterances and the test set contains 1,242 utterances. Source: Audio-visual Recognition of Overlapped speech for the LRS2 dataset Image Source: https://www.robots.ox.ac.uk/~vgg/data/lip_reading/lrs2.html
LRS3-TED is a multi-modal dataset for visual and audio-visual speech recognition. It includes face tracks from over 400 hours of TED and TEDx videos, along with the corresponding subtitles and word alignment boundaries. The new dataset is substantially larger in scale compared to other public datasets that are available for general research. Source: LRS3-TED: a large-scale dataset for visual speech recognition