Use of a Confusion Network to Detect and Correct Errors in an On-Line Handwritten Sentence Recognition System - Archive ouverte HAL
Communication Dans Un Congrès Année : 2007

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

Résumé

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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Dates et versions

hal-00582384 , version 1 (01-04-2011)

Identifiants

  • HAL Id : hal-00582384 , version 1

Citer

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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