Language-independent OCR using a continuous speech recognition system

Author

Schwartz, Richard ; LaPre, Christopher ; Makhoul, John ; Raphael, Christopher ; Zhao, Ying

Author_Institution

BBN Syst. & Technol. Corp., Cambridge, MA, USA

Volume

3

fYear

1996

fDate

25-29 Aug 1996

Firstpage

99

Abstract

In this paper we show how continuous speech recognition methods can be used for character recognition resulting in a technology that is language independent and does not require presegmentation of the data at the character and word levels. In multifont experiments on the ARPA Arabic OCR Corpus an average character error rate of 1.9% is obtained using the BBN BYBLOS continuous speech recognition system with no modifications. A first experiment using the identical system and procedures, trained and tested on a subset of the English Univ. of Washington OCR corpus resulted in 1.4% character error

Keywords

hidden Markov models; optical character recognition; speech recognition; ARPA Arabic OCR Corpus; BBN BYBLOS continuous speech recognition system; continuous speech recognition system; language-independent OCR; multifont experiments; Character recognition; Error analysis; Error correction; Hidden Markov models; Image segmentation; Natural languages; Optical character recognition software; Pattern recognition; Speech recognition; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1996., Proceedings of the 13th International Conference on

Conference_Location

Vienna

ISSN

1051-4651

Print_ISBN

0-8186-7282-X

Type

conf

DOI

10.1109/ICPR.1996.546802

Filename

546802