Title :
Visual Speech Recognition and Utterance Segmentation Based on Mouth Movement
Author :
Yau, Wai Chee ; Weghorn, Hans ; Kumar, Dinesh Kant
Abstract :
This paper presents a vision-based approach to recognize speech without evaluating the acoustic signals. The proposed technique combines motion features and support vector machines (SVMs) to classify utterances. Segmentation of utterances is important in a visual speech recognition system. This research proposes a video segmentation method to detect the start and end frames of isolated utterances from an image sequence. Frames that correspond to `speaking´ and `silence´ phases are identified based on mouth movement information. The experimental results demonstrate that the proposed visual speech recognition technique yields high accuracy in a phoneme classification task. Potential applications of such a system are, e.g., human computer interface (HCI) for mobility-impaired users, lip-reading mobile phones, in-vehicle systems, and improvement of speech-based computer control in noisy environments.
Keywords :
Acoustic signal detection; Application software; Computer interfaces; Image segmentation; Image sequences; Mouth; Speech analysis; Speech recognition; Support vector machine classification; Support vector machines;
Conference_Titel :
Digital Image Computing Techniques and Applications, 9th Biennial Conference of the Australian Pattern Recognition Society on
Conference_Location :
Glenelg, Australia
Print_ISBN :
0-7695-3067-2
DOI :
10.1109/DICTA.2007.4426769