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Inductive Inference in Non-Native Speech Processing and Learning.

机译:非母语语音处理和学习中的归纳推理。

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摘要

Despite extensive research on language acquisition, our understanding of how people learn abstract linguistic structures remains limited. In the phonological domain, we know that perceptual reorganization in infancy results in attuning to native language (L1) phonetic categories and, consequently, in difficulty discriminating and learning non-native categories. This difficulty has been proposed to originate from novel sounds being perceptually mapped onto L1 phonetic categories, leading to massive L1 interference. However, ample evidence that the adult speech processing system preserves a considerable degree of plasticity suggests that more complex learning mechanisms might be in place. In this dissertation I propose an alternative theory in which non-native speech processing is guided by principles of hierarchical inductive inference regarding how likely a given phonetic dimension is to be phonologically informative in any novel language. This theory differs crucially from mapping theories in predicting that when a phonetic dimension is informative (e.g., phonologically contrastive) in one's native language, discriminations involving that dimension should be enhanced even among classes of sounds for which the dimension is not informative in the native language. I provide experimental evidence supporting the inductive theory, demonstrating that language learning goes beyond the acquisition of specific phonetic categories, and includes higher-order generalizations regarding the relative importance of phonetic dimensions in the language as a whole. I argue that this theory can be extended beyond phonetic category learning to other domains of language acquisition, and that it suggests that adults and infants recruit the same domain-general learning mechanisms when acquiring novel languages.
机译:尽管对语言习得进行了广泛的研究,但我们对人们如何学习抽象语言结构的理解仍然有限。在语音领域,我们知道婴儿期的感知重组会导致对母语(L1)语音类别的调解,从而导致辨别和学习非本地类别的困难。已经提出这种困难是由于将新颖的声音被感知地映射到L1语音类别上,从而导致大量的L1干扰。但是,有足够的证据表明成人语音处理系统保留了相当大的可塑性,这表明可能存在更复杂的学习机制。在这篇论文中,我提出了一种替代性理论,其中非母语语音处理由层次归纳推理原理指导,该推理涉及在任何新颖语言中,给定的语音维度在语音上提供语音信息的可能性。该理论与映射理论的主要不同之处在于,它预测当一个语音维度在某人的母语中是信息性的(例如,语音上的对比)时,即使在该维度在母语中不具有信息性的声音类别之间,也应加强与该维度有关的区分。我提供了支持归纳理论的实验证据,证明了语言学习超越了特定语音类别的获取范围,并且包括有关语音维度在整个语言中的相对重要性的高阶概括。我认为该理论可以从语音类别学习扩展到语言习得的其他领域,并且它表明成年人和婴儿在习得新语言时会招募相同的领域通用学习机制。

著录项

  • 作者

    Pajak, Bozena.;

  • 作者单位

    University of California, San Diego.;

  • 授予单位 University of California, San Diego.;
  • 学科 Language Linguistics.;Psychology Cognitive.
  • 学位 Ph.D.
  • 年度 2012
  • 页码 144 p.
  • 总页数 144
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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