Segmental speech units such as phonemes are cued by multiple acoustic dimensions (e.g. F0 and duration), but dimensions do not carry equal perceptual weight. The relative perceptual weights of acoustic speech dimensions are not fixed but vary with context. For example, when speech is altered to create an ‘accent’ in which two acoustic dimensions are correlated in a manner opposite that of long-term experience, the dimension that carries less perceptual weight is down-weighted to contribute less in category decisions. It remains unclear, however, whether this short-term reweighting is limited to segmental categorization, or if it extends to categorization of suprasegmental features which span multiple phonemes, syllables, or words, which would suggest that such “dimension-based statistical learning” is a widespread phenomenon in speech perception. Here we investigated the relative contribution of two acoustic dimensions to word emphasis. Participants categorized instances of a two-word phrase pronounced with typical covariation of fundamental frequency (F0) and duration, and in the context of an artificial ‘accent’ in which F0 and duration (established in prior research on English speech as ‘primary’ and ‘secondary’ dimensions, respectively) covaried atypically. When categorizing ‘accented’ speech, listeners rapidly down-weighted the secondary dimension (duration) while continuing to rely on the primary dimension (F0). This result indicates that listeners continually track short-term regularities across speech input and dynamically adjust the weight of acoustic evidence for suprasegmental categories. Thus, dimension-based statistical learning appears to be a widespread phenomenon in speech perception extending to both segmental and suprasegmental categorization.

中文翻译：

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超分段分类中的短期感知重新加权

音素等分段语音单元由多个声学维度（例如 F0 和持续时间）提示，但维度不具有相同的感知权重。声学语音维度的相对感知权重不是固定的，而是随上下文变化的。例如，当语音被改变以创建一种“口音”时，其中两个声学维度以与长期经验相反的方式相关联，承载较少感知权重的维度被降低权重以减少类别决策的贡献。然而，目前尚不清楚这种短期重新加权是否仅限于分段分类，或者是否扩展到跨越多个音素、音节或单词的超分段特征的分类，这表明这种“基于维度的统计学习”是言语感知中的普遍现象。在这里，我们研究了两个声学维度对单词强调的相对贡献。参与者对两个词短语的实例进行分类，该短语的发音具有基本频率 (F0) 和持续时间的典型协变，并在人工“口音”的背景下进行分类，其中 F0 和持续时间（在先前关于英语语音的研究中确立为“主要”和'次要'维度，分别）非典型地协变。在对“重音”语音进行分类时，听众会迅速降低次级维度（持续时间）的权重，同时继续依赖主要维度 (F0)。这一结果表明，听众不断地跟踪语音输入的短期规律，并动态调整超音段类别的声学证据的权重。因此，