Abstract

Previous models of language acquisition have had partial success describing the processes that children use to acquire knowledge of the grammatical categories of their native language. The present study used a computer model based on the evolutionary principles of adaptation and selection to gain further insight into children's acquisition of grammatical categories. Transcribed language samples of eight parents or caregivers each conversing with their own child served as the input corpora for the model. The model was tested on each child's language corpus three times: two fixed mutation rates as well as a progressively decreasing mutation rate, which allowed less adaptation over time, were examined. The output data were evaluated by measuring the computer model's ability to correctly identify the grammatical categories in 500 utterances from the language corpus of each child. The model's performance ranged between 78 and 88 percent correct; the highest performance overall was found for a corpus using the progressively decreasing mutation rate, but overall no clear pattern relative to mutation rate was found.

Degree

MS

College and Department

David O. McKay School of Education; Communication Disorders

Rights

http://lib.byu.edu/about/copyright/

Date Submitted

2016-02-01

Document Type

Thesis

Handle

http://hdl.lib.byu.edu/1877/etd8333

Keywords

grammatical word categories, evolutionary programming, language acquisition

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