DocumentCode
419632
Title
Optimizing the integration of a statistical language model in HMM based offline handwritten text recognition
Author
Zimmermann, Matthias ; Bunke, Horst
Author_Institution
Dept. of Comput. Sci., Bern Univ., Switzerland
Volume
2
fYear
2004
fDate
23-26 Aug. 2004
Firstpage
541
Abstract
Although handwritten text recognition has been studied for some years, only few authors have used statistical language models to increase the performance of their recognizers. In those few cases where a language model has been used, its integration has not been systematically optimized. We investigate the optimization of the integration of statistical language models into HMM based recognition systems for offline handwritten text. Based on experiments with the IAM database we show that the recognition performance of a general offline handwritten text recognizer can be substantially improved.
Keywords
handwritten character recognition; hidden Markov models; optimisation; statistics; HMM based offline handwritten text recognition; IAM database; statistical language model; Computer science; Databases; Decoding; Feature extraction; Handwriting recognition; Hidden Markov models; Natural languages; Probability; Speech recognition; Text recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-2128-2
Type
conf
DOI
10.1109/ICPR.2004.1334297
Filename
1334297
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