Huge TED Video Collection Helps Computers Read Faces and Speech
Meet LRS3-TED, a large set of TED and TEDx clips made to teach machines to watch mouths and learn words.
It brings together face tracks from over 400 hours of TED and TEDx talks, with matching subtitles and exact word timing.
The goal is to push research in visual speech and audio-visual systems, so tools can use video, sound or both to understand what was said.
People making lip-reading apps, better captions, or tools for people who struggle to hear can use this data to train models faster.
Because clips include word boundaries, models learn when words start and stop, and that tends to boost accuracy.
It make large scale testing simple, so teams worldwide can try new ideas and fix real problems.
This is a big step toward computers that read faces and speech more like humans do, and it could help millions who rely on clear captions.
Read article comprehensive review in Paperium.net:
LRS3-TED: a large-scale dataset for visual speech recognition
🤖 This analysis and review was primarily generated and structured by an AI . The content is provided for informational and quick-review purposes.
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