A Computational Model for Taxonomy-Based Word Learning Inspired by Infant Developmental Word Acquisition(Biocybernetics, Neurocomputing)

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概要

• 論文の詳細を見る

• To develop human interfaces such as home information equipment, highly capable word learning ability is required. In particular, in order to realize user-customized and situation-dependent interaction using language, a function is needed that can build new categories online in response to presented objects for an advanced human interface. However, at present, there are few basic studies focusing on the purpose of language acquisition with category formation. In this study, taking hints from an analogy between machine learning and infant developmental word acquisition, we propose a taxonomy-based word-learning model using a neural network. Through computer simulations, we show that our model can build categories and find the name of an object based on categorization.

• 一般社団法人電子情報通信学会の論文
• 2005-10-01

著者

• Toyomura Akira

  Graduate School Of Engineering Hokkaido University

• Omori Takashi

  Graduate School Of Information Science And Technology Hokkaido University

関連論文

• Auditory feedback control during a sentence-reading task : Effect of other's voice
• A Computational Model for Taxonomy-Based Word Learning Inspired by Infant Developmental Word Acquisition(Biocybernetics, Neurocomputing)

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