
Proceedings Paper
Face and lip tracking in unconstrained imagery for improved automatic speech recognitionFormat | Member Price | Non-Member Price |
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Paper Abstract
When combined with acoustical speech information, visual speech information (lip movement) significantly improves
Automatic Speech Recognition (ASR) in acoustically noisy environments. Previous research has demonstrated that
visual modality is a viable tool for identifying speech. However, the visual information has yet to become utilized in
mainstream ASR systems due to the difficulty in accurately tracking lips in real-world conditions. This paper presents
our current progress in tracking face and lips in visually challenging environments. Findings suggest the mean shift
algorithm performs poorly for small regions, in this case the lips, but it achieves near 80% accuracy for facial tracking.
Paper Details
Date Published: 19 January 2009
PDF: 11 pages
Proc. SPIE 7257, Visual Communications and Image Processing 2009, 72571Y (19 January 2009); doi: 10.1117/12.817092
Published in SPIE Proceedings Vol. 7257:
Visual Communications and Image Processing 2009
Majid Rabbani; Robert L. Stevenson, Editor(s)
PDF: 11 pages
Proc. SPIE 7257, Visual Communications and Image Processing 2009, 72571Y (19 January 2009); doi: 10.1117/12.817092
Show Author Affiliations
Brandon Crow, California Polytechnic State Univ. (United States)
Jane Xiaozheng Zhang, California Polytechnic State Univ. (United States)
Published in SPIE Proceedings Vol. 7257:
Visual Communications and Image Processing 2009
Majid Rabbani; Robert L. Stevenson, Editor(s)
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