A long‐standing question in cognitive science is how high‐level knowledge is integrated with sensory input. For example, listeners can leverage lexical knowledge to interpret an ambiguous speech sound, but do such effects reflect direct top‐down influences on perception or merely postperceptual biases? A critical test case in the domain of spoken word recognition is lexically mediated compensation for coarticulation (LCfC). Previous LCfC studies have shown that a lexically restored context phoneme (e.g., /s/ in Christma#) can alter the perceived place of articulation of a subsequent target phoneme (e.g., the initial phoneme of a stimulus from a tapes‐capes continuum), consistent with the influence of an unambiguous context phoneme in the same position. Because this phoneme‐to‐phoneme compensation for coarticulation is considered sublexical, scientists agree that evidence for LCfC would constitute strong support for top–down interaction. However, results from previous LCfC studies have been inconsistent, and positive effects have often been small. Here, we conducted extensive piloting of stimuli prior to testing for LCfC. Specifically, we ensured that context items elicited robust phoneme restoration (e.g., that the final phoneme of Christma# was reliably identified as /s/) and that unambiguous context‐final segments (e.g., a clear /s/ at the end of Christmas) drove reliable compensation for coarticulation for a subsequent target phoneme. We observed robust LCfC in a well‐powered, preregistered experiment with these pretested items (N = 40) as well as in a direct replication study (N = 40). These results provide strong evidence in favor of computational models of spoken word recognition that include top–down feedback.

中文翻译：

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强大的词汇介导的协同发音补偿：圣诞节又来了

认知科学中一个长期存在的问题是高级知识如何与感官输入相结合。例如，听众可以利用词汇知识来解释模糊的语音，但这种效果是否反映了对感知的直接自上而下的影响，或者仅仅是感知后的偏见？口语单词识别领域的一个关键测试用例是词汇介导的协同发音补偿（LCfC）。先前的 LCfC 研究表明，词汇恢复的上下文音素（例如，Christma#中的 /s/ ）可以改变后续目标音素的感知发音位置（例如，来自Tape-Capes连续体的刺激的初始音素），与相同位置的明确上下文音素的影响一致。由于这种协同发音的音素到音素补偿被认为是潜词汇的，科学家们一致认为 LCfC 的证据将为自上而下的互动提供强有力的支持。然而，之前的 LCfC 研究结果并不一致，而且积极效果往往很小。在这里，我们在测试 LCfC 之前进行了广泛的刺激试验。具体来说，我们确保上下文项引发强大的音素恢复（例如， Christma#的最终音素被可靠地识别为 /s/）以及明确的上下文最终片段（例如，圣诞节结束时清晰的 /s/ ）为后续目标音素的发音提供可靠的补偿。我们在使用这些预先测试的项目进行的强有力的预先注册实验 ( N = 40) 以及直接复制研究 ( N = 40) 中观察到了稳健的 LCfC。这些结果为支持包括自上而下反馈的口语单词识别计算模型提供了强有力的证据。