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Use of a Confusion Network to Detect and Correct Errors in an On-Line Handwritten Sentence Recognition System
Abstract : In this paper we investigate the integration of a confusion network into an on-line handwritten sentence recognition system. The word posterior probabilities from the confusion network are used as confidence scored to detect potential errors in the output sentence from the Maximum A Posteriori decoding on a word graph. Dedicated classifiers (here, SVMs) are then trained to correct these errors and combine the word posterior probabilities with other sources of knowledge. A rejection phase is also introduced in the detection process. Experiments on handwritten sentences show a 28.5i% relative reduction of the word error rate.
Cited literature [9 references]
https://hal.archives-ouvertes.fr/hal-00582384
Contributor : Solen Quiniou Connect in order to contact the contributor
Submitted on : Friday, April 1, 2011 - 11:53:38 AM
Last modification on : Thursday, January 7, 2021 - 4:11:51 PM
Long-term archiving on: : Saturday, July 2, 2011 - 2:38:50 AM
Contributor : Solen Quiniou Connect in order to contact the contributor
Submitted on : Friday, April 1, 2011 - 11:53:38 AM
Last modification on : Thursday, January 7, 2021 - 4:11:51 PM
Long-term archiving on: : Saturday, July 2, 2011 - 2:38:50 AM
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quiniou07use.pdf
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