Unlearnable phonotactics
Unlearnable phonotactics
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DOI：
10.5334/gjgl.892
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发表时间：
2020-06-12
影响因子：
1
通讯作者：
Hestvik, Arild
中科院分区：
文献类型：
--
作者：
Avcu, Enes;Hestvik, Arild
次规则假说(Heinz 2010)指出，只有具有特定的次规则计算属性的模式在语音上是可学习的。Lai(2015)为这一假说提供了初步的实验室支持。目前的研究旨在通过使用不同的实验范式(古怪任务)和不同的学习测量(敏感性指数，d‘)来复制和扩展早期的发现。具体地说，我们比较了两种在计算和类型上不同的音位模式的可学性：一条简单的规则(“First-Last Converamation”)要求单词的第一段和最后一段一致(预计无法学习)，另一条是和声规则(“sibilant Harmony”)，要求整个单词的特征一致(预计是可学习的)。在两种实验条件下检验了第一-最后同化规则：一种是训练数据也符合同化同化规则，另一种是训练数据只符合第一-最后规则。与Lai(2015)的研究结果一样，我们发现被试对违反同化规则的敏感程度明显高于同化规则。然而，与Lai(2015)不同的是，我们也发现参与者对第一-最后规则表现出一些残留的敏感性，但这种敏感性与规则类型存在交互作用，因此参与者对违反SH规则的敏感性显著更高。我们的结论是，人工语法学习实验的参与者表现出普遍语法限制了他们的学习，但由于非语言学习机制，被预测为无法作为语言系统学习的模式仍然可以在一定程度上被学习。
The Subregular Hypothesis (Heinz 2010) states that only patterns with specific subregular computational properties are phonologically learnable. Lai (2015) provided the initial laboratory support for this hypothesis. The current study aimed to replicate and extend the earlier findings by using a different experimental paradigm (oddball task) and a different measure of learning (sensitivity index, d'). Specifically, we compared the learnability of two phonotactic patterns that differ computationally and typologically: a simple rule ("First-Last Assimilation") that requires agreement between the first and last segment of a word (predicted to be unlearnable), and a harmony rule ("Sibilant Harmony") that requires the agreement of features throughout the word (predicted to be learnable). The First-Last Assimilation rule was tested under two experimental conditions: one where the training data were also consistent with the Sibilant Harmony rule, and one where the training data were only consistent with the First-Last rule. As in Lai (2015), we found that participants were significantly more sensitive to violations of the Sibilant Harmony (SH) rule than to the First-Last Assimilation (FL) rules. However, unlike Lai (2015), we also found that participants showed some residual sensitivity to the First-Last rule, but that sensitivity interacted with rule type so that participants were significantly more sensitive to SH rule violations. We conclude that participants in Artificial Grammar Learning experiments exhibit evidence of Universal Grammar constraining their learning, but patterns predicted to be unlearnable as a linguistic system can still be learned to some degree, due to non-linguistic learning mechanisms.