Multi-font recognition of printed Arabic using the BBN BYBLOS speech recognition system
CHRISTOPHER LAPRE, Ying Zhao, C. Raphael, Richard M. Schwartz, J. Makhoul · 2002
We use a hidden Markov model (HMM) based continuous speech recognition system to perform off-line character recognition (OCR) of Arabic printed text. The HMM trainer and recognizer are used without change, however we modify the feature extraction stage to compute features relevant to OCR. Although we begin by segmenting the page into a collection of lines, no further segmentation is necessary for either recognition or training. Experiments on the ARPA Arabic data corpus yield a range of character error rates from under one percent for a single computer font to 2.8% for multiple-font recognition of a wide range of material from books, magazines and newspapers.