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
Link To Document :
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