LRS3-TED: a large-scale dataset for visual speech recognition
This provides a new benchmark for researchers in visual and audio-visual speech recognition, though it is incremental as it expands on existing dataset efforts.
The authors tackled the lack of large-scale datasets for visual speech recognition by introducing LRS3-TED, a multi-modal dataset with over 400 hours of TED and TEDx videos, face tracks, subtitles, and word alignment boundaries, which is substantially larger than existing public datasets.
This paper introduces a new 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.