A fundamental problem in speech perception is how (or whether) listeners accommodate variability in the way talkers produce speech. One view of the way listeners cope with this variability is that talker differences are normalized – a mapping between talker-specific characteristics and phonetic categories is computed such that speech is recognized in the context of the talker’s vocal characteristics. Consistent with this view, listeners process speech more slowly when the talker changes randomly than when the talker remains constant. An alternative view is that speech perception is based on talker-specific auditory exemplars in memory clustered around linguistic categories that allow talker-independent perception. Consistent with this view, listeners become more efficient at talker-specific phonetic processing after voice identification training. We asked whether phonetic efficiency would increase with talker familiarity by testing listeners with extremely familiar talkers (family members), newly familiar talkers (based on laboratory training), and unfamiliar talkers. We also asked whether familiarity would reduce the need for normalization. As predicted, phonetic efficiency (word recognition in noise) increased with familiarity (unfamiliar < trained-on < family). However, we observed a constant processing cost for talker changes even for pairs of family members. We discuss how normalization and exemplar theories might account for these results, and constraints the results impose on theoretical accounts of phonetic constancy.

语音感知中的一个基本问题是，听众如何（或是否）适应讲话者说话方式的可变性。倾听者应对这种变化的方式的一种观点是，将谈话者的差异归一化–计算讲话者特定特征与语​​音类别之间的映射，以便在讲话者的声音特征的上下文中识别语音。与该观点一致，当讲话者随机改变时，听者对语音的处理要比保持讲话者保持恒定时慢得多。另一种观点是，语音感知是基于记忆中的特定于谈话者的听觉范例，这些范例围绕着允许与谈话者无关的感知的语言类别而聚集。与该观点一致，在进行语音识别训练之后，听众在讲话者特定的语音处理方面变得更有效率。我们询问通过与非常熟悉的谈话者（家庭成员），新近熟悉的谈话者（基于实验室培训）和不熟悉的谈话者进行测试来提高听众的语音效率。我们还询问熟悉程度是否会减少标准化的需要。如预期的那样，语音效率（噪声中的单词识别）随着熟悉程度的提高（不熟悉<受过训练的<家庭）。但是，我们发现，即使是成对的家庭成员，谈话者变更的处理成本也是不变的。我们讨论归一化和范式理论如何解释这些结果，以及如何将结果强加于语音恒定性的理论解释上。