A Biologically Plausible SOM Representation of the Orthographic Form of 50,000 French Words

  • Claude Touzet
  • Christopher Kermorvant
  • Hervé Glotin
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 295)


Recently, an important aspect of human visual word recognition has been characterized. The letter position is encoded in our brain using an explicit representation of order based on letter pairs: the open-bigram coding [15]. We hypothesize that spelling has evolved in order to minimize reading errors. Therefore, word recognition using bigrams — instead of letters — should be more efficient. First, we study the influence of the size of the neighborhood, which defines the number of bigrams per word, on the performance of the matching between bigrams and word. Our tests are conducted against one of the best recognition solutions used today by the industry, which matches letters to words. Secondly, we build a cortical map representation of the words in the bigram space — which implies numerous experiments in order to achieve a satisfactory projection. Third, we develop an ultra-fast version of the self-organizing map in order to achieve learning in minutes instead of months.


Handwriting recognition word recognition open-bigram coding orthographic representation cortical representation 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Claude Touzet
    • 1
  • Christopher Kermorvant
    • 2
  • Hervé Glotin
    • 3
  1. 1.Aix-Marseille University (AMU), Lab. de Neurosciences Intégratives et AdaptativesLNIA UMR-CNRS 7260, Pôle Cerveau-Comportement-CognitionMarseilleFrance
  2. 2.A2iA SA (Analyse d’Image & Intelligence Artificielle)ParisFrance
  3. 3.Institut Univ. de France (IUF) & Univ. Aix-Marseille (AMU), Univ. Toulon (UTLN), ENSAM, Lab. des Sciences de l’Information et des Systèmes (LSIS)UMR CNRS 7296ToulonFrance

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