Title
Implementation of biases observed in children's language development into agents
Abstract
This paper describes efficient word meaning acquisition for infant agents (IAs) based on learning biases that are observed in children's language development. An IA acquires word meanings through learning the relations among visual features of objects and acoustic features of human speech. In this task, the IA has to find out which visual features are indicated by the speech. Previous works introduced stochastic approaches to do this, however, such approaches need many examples to achieve high accuracy. In this paper, firstly, we propose a word meaning acquisition method for the IA based on an Online-EM algorithm without learning biases. Then, we implement two types of biases into it to accelerate the word meaning acquisition. Experimental results show that the proposed method with biases can efficiently acquire word meanings.
Year
DOI
Venue
2006
10.1007/11880172_8
EELC
Keywords
Field
DocType
word meaning,language development,word meaning acquisition method,word meaning acquisition,efficient word meaning acquisition,acoustic feature,visual feature,human speech,online-em algorithm,em algorithm
Computer science,Natural language processing,Artificial intelligence,Language development
Conference
Volume
ISSN
ISBN
4211
0302-9743
3-540-45769-0
Citations 
PageRank 
References 
0
0.34
5
Authors
5
Name
Order
Citations
PageRank
Ryo Taguchi1338.10
Masashi Kimura201.35
Shuji Shinohara353.91
Kouichi Katsurada46917.35
Tsuneo Nitta514434.35