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Use of a Confusion Network to Detect and Correct Errors in an On-Line Handwritten Sentence Recognition System

Solen Quiniou 1, * Eric Anquetil 1
* Corresponding author
1 IMADOC - Interprétation et Reconnaissance d’Images et de Documents
UR1 - Université de Rennes 1, INSA Rennes - Institut National des Sciences Appliquées - Rennes, CNRS - Centre National de la Recherche Scientifique : UMR6074
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.
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https://hal.archives-ouvertes.fr/hal-00582384
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  • HAL Id : hal-00582384, version 1

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Solen Quiniou, Eric Anquetil. Use of a Confusion Network to Detect and Correct Errors in an On-Line Handwritten Sentence Recognition System. International Conference on Document Analysis and Recognition (ICDAR), Sep 2007, Curitiba, Brazil. pp.382-386. ⟨hal-00582384⟩

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