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

4 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

Other

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

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All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Sagheer, A. E., Tsuruta, N., & Taniguchi, R-I. (2004). Arabic lip-reading system: A combination of hypercolumn neural network model with hidden Markov model. In A. P. Pobil (Ed.), Proceedings of the Eighth IASTED International Conference On Artificial Intelligence and Soft Computing (pp. 311-316)