Challenge based visual speech recognition using deep learning

Philip McShane, Darryl Stewart

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a novel approach to liveness verification based on visual speech recognition within a challenge-based framework which has the potential to be used on mobile devices to prevent replay or spoof attacks during Face-based liveness verification. The system uses model visual speech recognition and determines liveness based on the Levenshtein Distance between a randomly generated challenge phrase and the hypothesis utterances from the visual speech recognizer. A Deep learning-based approach to visual speech recognition is used to improve upon the state of the art for the use of visual speech recognition for liveness verification.

Original languageEnglish
Title of host publication12th International Conference for Internet Technology and Secured Transactions (ICITST 2017): Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages405-410
Number of pages6
ISBN (Electronic)9781908320933
DOIs
Publication statusPublished - 10 May 2018
Event12th International Conference for Internet Technology and Secured Transactions, ICITST 2017 - Cambridge, United Kingdom
Duration: 11 Dec 201714 Dec 2017

Conference

Conference12th International Conference for Internet Technology and Secured Transactions, ICITST 2017
CountryUnited Kingdom
CityCambridge
Period11/12/201714/12/2017

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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