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LipNet

From Wikipedia, the free encyclopedia

LipNet is a deep neural network for audio-visual speech recognition (ASVR). It was created by University of Oxford researchers Yannis Assael, Brendan Shillingford, Shimon Whiteson, and Nando de Freitas.[1] The researchers stated that could match mouth movements to text with 93 percent accuracy,[2] though it was criticized for its test using a limited dataset of words and grammar.[3] It was used in Nvidia's autonomous "backseat driver" prototype Co-Pilot.[4]

References

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  1. Assael, Yannis M.; Shillingford, Brendan; Whiteson, Shimon; de Freitas, Nando (2016-12-16). "LipNet: End-to-End Sentence-level Lipreading". arXiv:1611.01599 [cs.LG].
  2. "AI that lip-reads 'better than humans'". BBC News. 2016-11-08. Retrieved 2026-05-25.
  3. Vincent, James (November 7, 2016). "Can deep learning help solve lip reading?". The Verge.
  4. Quach, Katyanna. "Revealed: How Nvidia's 'backseat driver' AI learned to read lips". www.theregister.com.