The Acquisition of Phonetic Categories: An Artificial Language Learning Study Public Deposited

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Last Modified
  • March 20, 2019
Creator
  • Moeng, Emily
    • Affiliation: College of Arts and Sciences, Department of Linguistics
Abstract
  • Part of learning a language includes determining what variation is meaningful and what variation is not meaningful. This dissertation presents a series of artificial language learning experiments to provide a timeline of early phonological acquisition in naïve adult learners. The core contribution of this dissertation is to propose a domain-general, two-stage model of distributional learning consisting of a Bias Stage followed by a Sensitivity Stage. Additionally, this dissertation will explore the relation that distributional learning holds with three factors, attention, environmental context, and lexical acquisition. Chapter 3 presents a set of experiments to make the core argument that distributional learning occurs in two stages. It is argued that the underlying mechanism behind distributional learning is not to directly warp the learner’s perceptual space, contrary to models which have been proposed. Chapter 3 will also examine the role of attention and its relation to distributional learning. Chapter 4 presents an experiment which investigates the relationship between environmental context and distributional learning. Results of this experiment will be used to support a one-stage model of allophony acquisition. Chapter 5 presents a set of experiments which explore the disparity between distributional learning and lexical acquisition.
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Rights statement
  • In Copyright
Advisor
  • Smith, Jennifer
  • Moreton, Elliott
  • Pertsova, Katya
  • Becker, Misha
  • Bergelson, Elika
  • Mielke, Jeff
Degree
  • Doctor of Philosophy
Degree granting institution
  • University of North Carolina at Chapel Hill Graduate School
Graduation year
  • 2018
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