Tag-assisted sentence confabulation for intelligent text recognition

Fan Yang, Qinru Qiu, Morgan Bishop, Qing Wu

Research output: Contribution to conferencePaper

3 Scopus citations

Abstract

Autonomous and intelligent recognition of printed or handwritten text image is one of the key features to achieve situational awareness. A neuromorphic model based intelligent text recognition (ITR) system has been developed in our previous work, which recognizes texts based on word level and sentence level context represented by statistical information of characters and words. While quite effective, sometimes the existing ITR system still generates results that are grammatically incorrect because it ignores semantic and syntactic properties of sentences. In this work, we improve the accuracy of the existing ITR system by incorporating parts-of-speech tagging into the text recognition procedure. Our experimental results show that the tag-assisted text recognition improves sentence level success rate by 33% in average.

Original languageEnglish (US)
DOIs
StatePublished - Oct 26 2012
Event2012 5th IEEE Symposium on Computational Intelligence for Security and Defence Applications, CISDA 2012 - Ottawa, ON, Canada
Duration: Jul 11 2012Jul 13 2012

Other

Other2012 5th IEEE Symposium on Computational Intelligence for Security and Defence Applications, CISDA 2012
CountryCanada
CityOttawa, ON
Period7/11/127/13/12

Keywords

  • cogent confabulation
  • parts-of-speech tagging
  • text recognition

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

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    Yang, F., Qiu, Q., Bishop, M., & Wu, Q. (2012). Tag-assisted sentence confabulation for intelligent text recognition. Paper presented at 2012 5th IEEE Symposium on Computational Intelligence for Security and Defence Applications, CISDA 2012, Ottawa, ON, Canada. https://doi.org/10.1109/CISDA.2012.6291521