Visual Speech Recognition Using Cepstral Images
Eun‐Jung Holden, Robyn A. Owens · UWA Profiles and Research Repository (University of Western Australia) · 2000
Automatic lipreading is important in various humancomputer interaction applications. Lipreading requires recognition not only of the mouth shape change but also of the appearance of the inner mouth (the teeth and the tongue). We have developed a lipreading system that can represent the changes of the mouth shape and the inner mouth appearance occurring throughout the input image sequence by producing a single 70 dimensional feature vector. This is achieved by generating the Cepstral coefficients of the pixel intensity change over time and arranging them as pixel intensities of a Cepstral image. Then the Higher Order Local Autocorrelation (HLAC) features are extracted from the Cepstral images and are used for classification. This paper explains the techniques used in the system, and reports on our feasibility study on the use of these techniques in automated lipreading.