Arabic Lip-reading System: A Combination of Hypercolumn Neural Network Model with Hidden Markov Model
Alaa Sagheer, Naoyuki Tsuruta, 直之 鶴田, Rin-ichiro Taniguchi, 倫一郎 谷口, サギール アラー, ナオユキ ツルタ, リンイチロウ タニグチ · Kyushu University Institutional Repository (QIR) (Kyushu University) · 2004
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).