Department of East Asian Languages and Literatures, University of Oregon, Eugene, OR 97403, USA.
J Exp Psychol Hum Percept Perform. 2011 Dec;37(6):1939-56. doi: 10.1037/a0025641. Epub 2011 Oct 17.
Speech processing requires sensitivity to long-term regularities of the native language yet demands listeners to flexibly adapt to perturbations that arise from talker idiosyncrasies such as nonnative accent. The present experiments investigate whether listeners exhibit dimension-based statistical learning of correlations between acoustic dimensions defining perceptual space for a given speech segment. While engaged in a word recognition task guided by a perceptually unambiguous voice-onset time (VOT) acoustics to signal beer, pier, deer, or tear, listeners were exposed incidentally to an artificial "accent" deviating from English norms in its correlation of the pitch onset of the following vowel (F0) to VOT. Results across four experiments are indicative of rapid, dimension-based statistical learning; reliance on the F0 dimension in word recognition was rapidly down-weighted in response to the perturbation of the correlation between F0 and VOT dimensions. However, listeners did not simply mirror the short-term input statistics. Instead, response patterns were consistent with a lingering influence of sensitivity to the long-term regularities of English. This suggests that the very acoustic dimensions defining perceptual space are not fixed and, rather, are dynamically and rapidly adjusted to the idiosyncrasies of local experience, such as might arise from nonnative-accent, dialect, or dysarthria. The current findings extend demonstrations of "object-based" statistical learning across speech segments to include incidental, online statistical learning of regularities residing within a speech segment.
语音处理需要对母语的长期规律保持敏感，但同时要求听众能够灵活适应说话者特征（如非母语口音）所产生的干扰。本实验研究了听众是否表现出基于维度的统计学习，即对定义特定语音段感知空间的声学维度之间的相关性进行学习。在一项由感知上明确的语音起始时间（VOT）声学引导的单词识别任务中，参与者听到的是 beer、pier、deer 或 tear 等词，同时，他们也会偶然接触到一种人为的“口音”，这种口音与英语规范不同，它的下一个元音（F0）起始音与 VOT 的相关性存在偏差。四个实验的结果表明，听众能够快速进行基于维度的统计学习；在识别单词时，对 F0 维度的依赖会迅速减弱，以应对 F0 和 VOT 维度之间相关性的干扰。然而，听众并没有简单地反映短期输入统计数据。相反，反应模式与对英语长期规律的敏感性的持久影响一致。这表明，定义感知空间的声学维度并非固定不变，而是可以动态快速地适应本地经验的特征，例如可能由非母语口音、方言或发音障碍引起的特征。目前的发现将“基于对象”的统计学习在语音段上的演示扩展到包括对语音段内规律的偶然、在线统计学习。
