Nevertheless, it persists: Dimension-based statistical learning and normalization of speech impact different levels of perceptual processing
Nevertheless, it persists: Dimension-based statistical learning and normalization of speech impact different levels of perceptual processing
复制标题
DOI：
10.1016/j.cognition.2020.104328
复制
发表时间：
2020-09-01
期刊：
影响因子：
3.4
通讯作者：
Holt, Lori L.
中科院分区：
文献类型：
--
作者：
Lehet, Matthew;Holt, Lori L.
众所周知，语音是可变的，没有从声学到单词和音素等具有语言意义的单位的简单映射。对这一理论中心问题的实证研究建立了至少两类适应声学变化的感知现象：归一化和感知学习。有趣的是，感知学习是通过跨声学变异性的学习来支持的，但归一化被认为可以抵消声学变异性，从而留下了关于这两种现象如何相互作用的悬而未决的问题。在这里，我们研究归一化和感知学习对声学维度如何映射到元音类别的联合影响。当听众将非单词分类为 setch 或 satch 时，他们经历了元音声学维度上短期分布规律的变化。这种“人工口音”的引入导致元音持续时间在分类中的贡献发生了变化。尽管这种基于维度的统计学习影响了元音持续时间对元音分类的影响，但这些完全相同的元音的持续时间仍然通过持续时间对比（一种标准化形式）对后续辅音的分类保持一致的影响。因此，元音持续时间具有与标准化和感知学习在处理层次结构中不同级别上运行一致的双重作用。我们假设，虽然标准化是跨听觉维度进行的，但基于维度的统计学习会影响听觉维度和语音类别之间的连接权重。
Speech is notoriously variable, with no simple mapping from acoustics to linguistically-meaningful units like words and phonemes. Empirical research on this theoretically central issue establishes at least two classes of perceptual phenomena that accommodate acoustic variability: normalization and perceptual learning. Intriguingly, perceptual learning is supported by learning across acoustic variability, but normalization is thought to counteract acoustic variability leaving open questions about how these two phenomena might interact. Here, we examine the joint impact of normalization and perceptual learning on how acoustic dimensions map to vowel categories. As listeners categorized nonwords as setch or satch, they experienced a shift in short-term distributional regularities across the vowels' acoustic dimensions. Introduction of this 'artificial accent' resulted in a shift in the contribution of vowel duration in categorization. Although this dimension-based statistical learning impacted the influence of vowel duration on vowel categorization, the duration of these very same vowels nonetheless maintained a consistent influence on categorization of a subsequent consonant via duration contrast, a form of normalization. Thus, vowel duration had a duplex role consistent with normalization and perceptual learning operating on distinct levels in the processing hierarchy. We posit that whereas normalization operates across auditory dimensions, dimension-based statistical learning impacts the connection weights among auditory dimensions and phonetic categories.