model,7-1-N03-1018,ak systems . In this paper , we introduce a <term> generative probabilistic optical character recognition ( OCR ) model </term> that describes an end-to-end process
other,23-1-N03-1018,ak describes an end-to-end process in the <term> noisy channel framework </term> , progressing from <term> generation
tech,29-1-N03-1018,ak framework </term> , progressing from <term> generation of true text </term> through its transformation into the
other,38-1-N03-1018,ak through its transformation into the <term> noisy output </term> of an <term> OCR system </term> . The
tech,42-1-N03-1018,ak the <term> noisy output </term> of an <term> OCR system </term> . The <term> model </term> is designed
model,1-2-N03-1018,ak </term> of an <term> OCR system </term> . The <term> model </term> is designed for use in <term> error
tech,7-2-N03-1018,ak model </term> is designed for use in <term> error correction </term> , with a focus on <term> post-processing
tech,14-2-N03-1018,ak correction </term> , with a focus on <term> post-processing </term> the <term> output </term> of <term> black-box
other,16-2-N03-1018,ak on <term> post-processing </term> the <term> output </term> of <term> black-box OCR systems </term>
tech,18-2-N03-1018,ak post-processing </term> the <term> output </term> of <term> black-box OCR systems </term> in order to make it more useful for
tech,29-2-N03-1018,ak in order to make it more useful for <term> NLP tasks </term> . We present an implementation of
model,6-3-N03-1018,ak We present an implementation of the <term> model </term> based on <term> finite-state models
model,9-3-N03-1018,ak implementation of the <term> model </term> based on <term> finite-state models </term> , demonstrate the <term> model 's </term>
model,14-3-N03-1018,ak finite-state models </term> , demonstrate the <term> model 's </term> ability to significantly reduce <term>
measure(ment),20-3-N03-1018,ak </term> ability to significantly reduce <term> character and word error rate </term> , and provide evaluation results
tech,31-3-N03-1018,ak provide evaluation results involving <term> automatic extraction </term> of <term> translation lexicons </term>
lr,34-3-N03-1018,ak <term> automatic extraction </term> of <term> translation lexicons </term> from printed <term> text </term> . We
other,38-3-N03-1018,ak translation lexicons </term> from printed <term> text </term> . We present an application of <term>
skrij podrobnosti