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Proceedings Paper

Lip reading using neural networks
Author(s): Dhananjay Kalbande; Sanjivani Patil
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Paper Abstract

Computerized lip reading, or speech reading, is concerned with the difficult task of converting a video signal of a speaking person to written text. It has several applications like teaching deaf and dumb to speak and communicate effectively with the other people, its crime fighting potential and invariance to acoustic environment. We convert the video of the subject speaking vowels into images and then images are further selected manually for processing. However, several factors like fast speech, bad pronunciation, and poor illumination, movement of face, moustaches and beards make lip reading difficult. Contour tracking methods and Template matching are used for the extraction of lips from the face. K Nearest Neighbor algorithm is then used to classify the 'speaking' images and the 'silent' images. The sequence of images is then transformed into segments of utterances. Feature vector is calculated on each frame for all the segments and is stored in the database with properly labeled class. Character recognition is performed using modified KNN algorithm which assigns more weight to nearer neighbors. This paper reports the recognition of vowels using KNN algorithms

Paper Details

Date Published: 30 September 2011
PDF: 7 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 828519 (30 September 2011); doi: 10.1117/12.913406
Show Author Affiliations
Dhananjay Kalbande, Sardar Patel Institute of Technology (India)
Sanjivani Patil, Sardar Patel Institute of Technology (India)

Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)
Yi Xie; Yanjun Zheng, Editor(s)

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