Presentation 2005/12/14
A Learning Mechanism of Word Meanings Based on the Online-EM algorithm and Application of Learning Biases
Ryo Taguchi, Masashi Kimura, Shuji Shinohara, Kouichi Katsurada, Tsuneo Nitta,
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Abstract(in English) This paper describes efficient concept acquisition for an infant agent (IA) based on learning bias, or constraint, that is observed in human infant learning. Previous concept acquisition systems calculate probabilities to identify the correct attributes that each object has, however, such approaches need much examples to achieve high accuracy. In this paper, we propose to incorporate learning biases into the learning stage of a concept acquisition system based on an online-EM algorithm. The experimental results show that the proposed method can achieve efficient learning.
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Keyword(in English) Learning of Word Meaning / Online-EM Algorithm / Learning Biases / Infant Agent
Paper # NLC2005-60,SP2005-93
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Committee NLC
Conference Date 2005/12/14(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) A Learning Mechanism of Word Meanings Based on the Online-EM algorithm and Application of Learning Biases
Sub Title (in English)
Keyword(1) Learning of Word Meaning
Keyword(2) Online-EM Algorithm
Keyword(3) Learning Biases
Keyword(4) Infant Agent
1st Author's Name Ryo Taguchi
1st Author's Affiliation Graduate School of Engineering, Toyohashi University of Technology()
2nd Author's Name Masashi Kimura
2nd Author's Affiliation Graduate School of Engineering, Toyohashi University of Technology
3rd Author's Name Shuji Shinohara
3rd Author's Affiliation Graduate School of Engineering, Toyohashi University of Technology
4th Author's Name Kouichi Katsurada
4th Author's Affiliation Graduate School of Engineering, Toyohashi University of Technology
5th Author's Name Tsuneo Nitta
5th Author's Affiliation Graduate School of Engineering, Toyohashi University of Technology
Date 2005/12/14
Paper # NLC2005-60,SP2005-93
Volume (vol) vol.105
Number (no) 493
Page pp.pp.-
#Pages 6
Date of Issue