Some languages, such as many varieties of English, use short-lag and long-lag VOT to distinguish word- and syllable-initial voiced vs. voiceless stop phonemes. According to a popular view, the optimal VOT category boundary between the two types of stops moves towards larger values as articulation rate becomes slower (and speech segments longer), and listeners accordingly shift the perceptual VOT category boundary. According to an alternative view, listeners do not shift the VOT category boundary with a change in articulation rate, because the same category boundary remains optimal across different rates of articulation in normal speech, although a shift in the optimal boundary location can be induced in the laboratory by instructing speakers to use artificially extreme articulation rates. In this study we compared the effectiveness of rate-independent VOT category boundaries applied to word-initial stop phonemes in spontaneous English speech, against the effectiveness of Miller et al.’s (1986) rate-dependent VOT category boundary applied to laboratory speech. The effectiveness of the two types of category boundaries were comparable, when spontaneous speech data were controlled for factors other than articulation rate. Our results suggest that perceptual VOT category boundaries need not shift with a change in articulation rate under normal circumstances.

中文翻译：

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词首停止中的 VOT 类别边界：反对英语自发语音速率归一化的反证

一些语言，例如许多种类的英语，使用短滞后和长滞后 VOT 来区分词和音节开头的浊音和清音停止音素。根据流行的观点，随着发音速度变慢（和语音段变长），两种类型的停顿之间的最佳 VOT 类别边界向更大的值移动，并且听众相应地移动感知 VOT 类别边界。根据另一种观点，听者不会随着发音速度的变化而移动 VOT 类别边界，因为相同的类别边界在正常语音中的不同发音速度之间保持最佳，尽管最佳边界位置的变化可以在实验室通过指示演讲者使用人为的极端发音率。在这项研究中，我们比较了应用于自发英语语音中词首停止音素的与速率无关的 VOT 类别边界的有效性，与应用于实验室语音的 Miller 等人 (1986) 速率相关的 VOT 类别边界的有效性。当自发语音数据被控制在发音率以外的因素时，这两种类别边界的有效性是可比的。我们的结果表明，在正常情况下，感知 VOT 类别边界不需要随着清晰度的变化而变化。当自发语音数据被控制为发音率以外的因素时，两种类别边界的有效性是可比的。我们的结果表明，在正常情况下，感知 VOT 类别边界不需要随着清晰度的变化而变化。当自发语音数据被控制在发音率以外的因素时，这两种类别边界的有效性是可比的。我们的结果表明，在正常情况下，感知 VOT 类别边界不需要随着清晰度的变化而变化。