On-line cursive handwriting recognition using speech recognition methods (1994)
| Venue: | In ICASSP |
| Citations: | 35 - 5 self |
BibTeX
@INPROCEEDINGS{Makhoul94on-linecursive,
author = {John Makhoul and Thad Starner and Richard Schwartz and George Chou},
title = {On-line cursive handwriting recognition using speech recognition methods},
booktitle = {In ICASSP},
year = {1994},
pages = {125--128}
}
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Abstract
The BYBLOS continuous speech recognition system is applied to on-line cursive handwriting recognition. By exploiting similarities between on-line cursive handwriting and continuous speech recogni-tion, we can use the same base system adapted to handwriting feature vectors instead of speech. The use of hidden Markov models obvi-ates the need for segmentation of the handwritten script sentences before recognition. To test our system, we collected handwritten sentences using text from the ARPA Airline Travel Information Ser-vice (ATIS) and the ARPA Wall Street Journal (WSJ) corpora. In an initial experiment on the ATIS data, a word error rate of 1.1 % was achieved with a 3050-word lexicon, 52-character set, collected from one writer. In a subsequent writer-dependent test on the WSJ data, error rates ranging between 2%-5 % were obtained with a 25,595-word lexicon, 86-character set, collected from six different writers. Details of the recognition system, the data collection process, and analysis of the experiments are presented. I.
