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VISUAL ARTIFICIAL GRAMMAR LEARNING: COMPARATIVE RESEARCH ON HUMANS AND BIRDS

机译：视觉人工语法学习：人与鸟类的比较研究

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Artificial grammar learning (AGL) can be a useful tool for exploring rule learning strategies linked to pattern perception and pattern rule learning, a prerequisite for language acquisition. Most AGL studies reasonably make use of sequentially presented acoustic strings, resulting in stimuli that in their composition resemble human speech. To overcome possible working memory constraints imposed by sequential string presentation and to thus be able to directly compare performance of humans to other species with different memory capacities, we developed an AGL task in the visual domain. Presenting visual pattern elements simultaneously instead of sequentially minimizes the amount of required working memory. This approach allowed us to evaluate performance levels of two bird species, kea (Nestor notabilis) and pigeons (Columba livia), in direct comparison to human subjects. All avian and human subjects were able to learn pattern regularities without explicit instructions and generalised learned rules to novel stimuli. Detailed testing suggests that birds and humans did not always acquire the same pattern rule, and birds made use of alternative strategies to those defined by the experimenters.
机译：人工语法学习（AGL）可以探索规则学习挂模式感知和形式规则的学习，语言习得的前提战略的有用工具。大多数AGL研究合理利用依次呈现声音的字符串，导致刺激，在其组成类似人类的语言。为了克服连续串呈现征收可能工作内存的限制，并因此能够对人类与其他物种具有不同内存容量的直接比较性能，我们开发了可视化领域的AGL任务。呈现视觉图案元件同时而不是顺序地减少所需的工作存储器的量。这种方法使我们能够评估两种鸟类，KEA（内斯特notabilis）和鸽子（科伦巴利维娅）的性能水平，在直接比较人类受试者。所有禽类和人类受试者能够学习模式规律没有明确的说明和推广学会规则，新刺激。详细的测试表明，鸟类和人类并不总是获得相同的模式规则，鸟类利用的替代策略，这些实验者定义。

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