At the computational level, language is often assumed to require both supervised and unsupervised learning. Although we have a certain understanding of these computational processes both biologically and behaviorally, our understanding of the environmental conditions under which language learning takes place falls short. I examine the semi-supervised learning paradigm as the most accurate computational description of the environmental conditions of lexical acquisition during language development. This paradigm is assessed for task learning and generalization and I argue that its real ecological validity and occasional improvements in performance over supervised learning make it an ideal candidate for modeling of language acquisition and other learning problems.
|Advisor:||Melara, Robert D.|
|Commitee:||Chodorow, Martin, Ji, Heng, Marshall, James B., Tartter, Vivien C.|
|School:||City University of New York|
|School Location:||United States -- New York|
|Source:||DAI-B 71/11, Dissertation Abstracts International|
|Subjects:||Developmental psychology, Cognitive psychology, Computer science|
|Keywords:||Connectionism, Language acquisition, Lexical acquisition, Neural networks, Semi-supervised learning|
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