Adaptive Plasticity in Speech Perception: Effects of External Information and Internal Predictions
Adaptive Plasticity in Speech Perception: Effects of External Information and Internal Predictions
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DOI：
10.1037/xhp0000196
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发表时间：
2016-07-01
影响因子：
2.1
通讯作者：
Holt, Lori L.
中科院分区：
文献类型：
--
作者：
Guediche, Sara;Fiez, Julie A.;Holt, Lori L.
当听者在不利的听力条件下遇到讲话时，感知上的适应性调整可以随着时间的推移提高理解能力。在某些情况下，这些自适应变化需要外部信息的存在来消除扭曲的语音信号的歧义，而在其他情况下，仅仅暴露就足够了。外部（如书面反馈）和内部（如先前的单词知识）信息源都可以用来对扭曲的语音信号的正确映射产生预测。我们假设这些预测为确定预期和实际语音信号之间的差异提供了基础，这些差异可用于指导感知的适应性变化。本研究提供了第一个通过以下方式操纵外部和内部因素的实证研究：(a)通过存在或不存在与退化刺激配对的反应后正字法信息来获得明确的外部消歧义信息，以及(b)内部生成预测的准确性；声波畸变的产生可能是突然的，也可能是逐渐的。结果表明，外部信息对适应性可塑性的影响取决于刺激的可理解性是否允许在暴露期间准确的内部生成预测。只有当输入信号严重退化，无法可靠地访问内部预测时，外部信息源才会增强自适应可塑性。这与自适应可塑性的计算框架是一致的，其中错误驱动的监督学习依赖于计算来自内部和外部信息源的感官预测误差信号的能力。
When listeners encounter speech under adverse listening conditions, adaptive adjustments in perception can improve comprehension over time. In some cases, these adaptive changes require the presence of external information that disambiguates the distorted speech signals, whereas in other cases mere exposure is sufficient. Both external (e.g., written feedback) and internal (e.g., prior word knowledge) sources of information can be used to generate predictions about the correct mapping of a distorted speech signal. We hypothesize that these predictions provide a basis for determining the discrepancy between the expected and actual speech signal that can be used to guide adaptive changes in perception. This study provides the first empirical investigation that manipulates external and internal factors through (a) the availability of explicit external disambiguating information via the presence or absence of postresponse orthographic information paired with a repetition of the degraded stimulus, and (b) the accuracy of internally generated predictions; an acoustic distortion is introduced either abruptly or incrementally. The results demonstrate that the impact of external information on adaptive plasticity is contingent upon whether the intelligibility of the stimuli permits accurate internally generated predictions during exposure. External information sources enhance adaptive plasticity only when input signals are severely degraded and cannot reliably access internal predictions. This is consistent with a computational framework for adaptive plasticity in which error-driven supervised learning relies on the ability to compute sensory prediction error signals from both internal and external sources of information.