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Bimodal Incremental Self-Organizing Network (BiSON) with Application to Learning Chinese Characters

  • Andrew P. Papliński
  • William M. Mount
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8226)

Abstract

We present a recurrent learning system that can incrementally integrate stimuli in two modalities, visual and auditory. The system consists of five self-organizing modules, each mapping input stimuli into respective latent spaces. Two sensory modules convert the input stimuli into an internal 3-D “neuronal code”. The central module integrates the bimodal information, and through modulatory top-down feedback influences the organization of data in two unimodal association units. Two feedback gains control the strength of the feedback connection. As an example we selected a set of Chinese characters and related spoken words. It is shown that the learning system can build a stable neuronal structure for incrementally applied visual and auditory stimuli.

Keywords

Multimodal Learning Visual and Auditory stimuli Recurrent networks Self-organization Chinese characters 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Andrew P. Papliński
    • 1
  • William M. Mount
    • 2
  1. 1.Monash UniversityAustralia
  2. 2.University of New South WalesAustralia

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