How linguistic chickens help spot spoken-eggs: phonological constraints on speech identification.
How linguistic chickens help spot spoken-eggs: phonological constraints on speech identification.
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DOI：
10.3389/fpsyg.2011.00182
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发表时间：
2011
影响因子：
3.8
通讯作者：
Vaknin-Nusbaum V
中科院分区：
文献类型：
--
作者：
Berent I;Balaban E;Vaknin-Nusbaum V
人们早就知道，将听觉刺激识别为语音是依赖于上下文的（Remez等人，）。在这里，我们表明，从他们的非语音变换的语音刺激的歧视进一步调制的语言结构。我们衡量的影响，语音结构上的歧视，在两种不同的语言中的不同表现形式良好。一个案例研究了对英语音节的限制（例如，格式良好的melif与格式不良的mlif）;另一个通过比较格式不良的AAB词干来研究对希伯来语词干的约束（例如，TiTuG）与格式良好的ABB和ABC控件（例如，GiTuT、MiGuS）。在这两种情况下，非语音刺激符合良好的结构是更难区分语音比刺激符合不良结构。辅助实验排除了这种现象的其他声学解释。在英语中，我们表明，模仿mlif-melif对比度的声学操作不会损害结构良好的非语音刺激的分类（即，双音节，发音短而长主音元音）。同样，非言语刺激，在希伯来语中是病态的，目前没有困难的英语发言者。因此，只有当非言语刺激在参与者的母语中形成良好时，它们才更难分类。我们的结论是，非语音刺激的分类调制的语言结构：输入，支持形式良好的输出更容易被归类为语音。
It has long been known that the identification of aural stimuli as speech is context-dependent (Remez et al.,). Here, we demonstrate that the discrimination of speech stimuli from their non-speech transforms is further modulated by their linguistic structure. We gauge the effect of phonological structure on discrimination across different manifestations of well-formedness in two distinct languages. One case examines the restrictions on English syllables (e.g., the well-formed melif vs. ill-formed mlif); another investigates the constraints on Hebrew stems by comparing ill-formed AAB stems (e.g., TiTuG) with well-formed ABB and ABC controls (e.g., GiTuT, MiGuS). In both cases, non-speech stimuli that conform to well-formed structures are harder to discriminate from speech than stimuli that conform to ill-formed structures. Auxiliary experiments rule out alternative acoustic explanations for this phenomenon. In English, we show that acoustic manipulations that mimic the mlif–melif contrast do not impair the classification of non-speech stimuli whose structure is well-formed (i.e., disyllables with phonetically short vs. long tonic vowels). Similarly, non-speech stimuli that are ill-formed in Hebrew present no difficulties to English speakers. Thus, non-speech stimuli are harder to classify only when they are well-formed in the participants’ native language. We conclude that the classification of non-speech stimuli is modulated by their linguistic structure: inputs that support well-formed outputs are more readily classified as speech.
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