JOURNAL ARTICLE

Exploring Lexical Network Development in Second Language Learners.

Scott A. CrossleyJulian E. BoggessThomas Lee Salsbury

Year: 2009 Journal:   The Florida AI Research Society Vol: 140 (898)Pages: 107-27

Abstract

This study explores how neural network models can simulate word production in second language (L2) learners. A neural network was trained to simulate L2 word production using a variety of word properties related to connectionist networks (hypernymy, polysemy, concreteness, and meaningfulness). The study demonstrates that a neural network can produce words to a similar degree as L2 learners. The findings are important for theories of L2 lexical growth and production.

Keywords:
Polysemy Computer science Concreteness Variety (cybernetics) Natural language processing Artificial intelligence Artificial neural network Connectionism Word (group theory) Production (economics) Vocabulary development Linguistics Vocabulary Psychology Cognitive psychology

Metrics

2
Cited By
2.11
FWCI (Field Weighted Citation Impact)
27
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Second Language Acquisition and Learning
Social Sciences →  Psychology →  Developmental and Educational Psychology
Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence

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