Universität zu Köln

Cao, Mengxue, Li, Aijun, Fang, Qiang, Kaufmann, Emily and Kroeger, Bernd J. (2014). Interconnected growing self-organizing maps for auditory and semantic acquisition modeling. Front. Psychol., 5. LAUSANNE: FRONTIERS MEDIA SA. ISSN 1664-1078

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Abstract

Based on the incremental nature of knowledge acquisition, in this study we propose a growing self-organizing neural network approach for modeling the acquisition of auditory and semantic categories. We introduce an Interconnected Growing Self-Organizing Maps (I-GSOM) algorithm, which takes associations between auditory information and semantic information into consideration, in this paper. Direct phonetic semantic association is simulated in order to model the language acquisition in early phases, such as the babbling and imitation stages, in which no phonological representations exist. Based on the I-GSOM algorithm, we conducted experiments using paired acoustic and semantic training data. We use a cyclical reinforcing and reviewing training procedure to model the teaching and learning process between children and their communication partners. A reinforcing-by-link training procedure and a link-forgetting procedure are introduced to model the acquisition of associative relations between auditory and semantic information. Experimental results indicate that (1) I-GSOM has good ability to learn auditory and semantic categories presented within the training data; (2) clear auditory and semantic boundaries can be found in the network representation; (3) cyclical reinforcing and reviewing training leads to a detailed categorization as well as to a detailed clustering, while keeping the clusters that have already been learned and the network structure that has already been developed stable; and (4) reinforcing-by-link training leads to well-perceived auditory semantic associations. Our I-GSOM model suggests that it is important to associate auditory information with semantic information during language acquisition. Despite its high level of abstraction, our I-GSOM approach can be interpreted as a biologically-inspired neurocomputational model.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Cao, Mengxue UNSPECIFIED UNSPECIFIED UNSPECIFIED Li, Aijun UNSPECIFIED UNSPECIFIED UNSPECIFIED Fang, Qiang UNSPECIFIED UNSPECIFIED UNSPECIFIED Kaufmann, Emily UNSPECIFIED UNSPECIFIED UNSPECIFIED Kroeger, Bernd J. UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-443212
DOI:	10.3389/fpsyg.2014.00236
Journal or Publication Title:	Front. Psychol.
Volume:	5
Date:	2014
Publisher:	FRONTIERS MEDIA SA
Place of Publication:	LAUSANNE
ISSN:	1664-1078
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language EARLY LEXICAL DEVELOPMENT; HUMAN SPEECH; NETWORK; ORGANIZATION; BIRDSONG Multiple languages Psychology, Multidisciplinary Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/44321