Arabic Lip-reading System: A Combination of Hypercolumn Neural Network Model with Hidden Markov Model
Year: 2004
Type: conference-paper
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).
Institutions: Kyushu University, Fukuoka University
Language: English
Topic: Speech and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2279438900