Arabic lip-reading system: A combination of hypercolumn neural network model with hidden Markov model

Alaa El Sagheer, Naoyuki Tsuruta, Rin Ichiro Taniguchi

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

5 Citations (Scopus)

Abstract

In recent year, lip-reading systems have received much attention, since it plays an important role in human communication with computer especially for hearing impaired or elderly people. In this paper, we introduce a new visual feature representation combines the Hypercolumn Neural Network model (HCM) with Hidden Markov Model (HMM) to achieve a complete lip-reading system. To check our system performance we introduce the Arabic language to it. According to our knowledge, this is the first time that a visual speech recognition system is applied for Arabic language. Experiments include different Arabic sentences gathered from different native speakers (Male & Female).

Original languageEnglish
Title of host publicationProceedings of the Eighth IASTED International Conference On Artificial Intelligence and Soft Computing
EditorsA.P. Pobil
Pages311-316
Number of pages6
Publication statusPublished - 2004
EventProceedings of the Eighth IASTED International Conference on Atificial Intelligence and Soft Computing - Marbella, Spain
Duration: Sep 1 2004Sep 3 2004

Publication series

NameProceedings of the Eighth IASTED International Conference on Artificial Intelligence and Soft Computing

Other

OtherProceedings of the Eighth IASTED International Conference on Atificial Intelligence and Soft Computing
CountrySpain
CityMarbella
Period9/1/049/3/04

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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