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Enhancing Human Cross-Linguistic Comprehension via Cognitive Computation and Selective Attention

机译:通过认知计算和选择性注意提高人类的跨语言理解

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Traditionally, perceptual salience for acoustic stimuli has a lower-level grounding in human cognitive mechanism and will not be influenced by linguistic traits. However, the striking difference of perceptual accuracy performances from the behavioral data has shown that higher-level neural processing should participate and offer crucial positive impact on human's cross-linguistic learning experience, and therefore influence the learning outcome. In this paper, we investigate the relationship between the efficiency of the second language (L2) perception and such high-level mechanism of human voluntary attention. Our findings lead to a revision to existing statistical model predictions through accuracy and reaction-time measurements with different attention conditions. They also suggest that enhancement of learning and memory of L2 would be achieved by efficient exploitation of the auxiliary attention pattern in the process of human cognition.
机译:传统上,听觉刺激的感知显着性在人类认知机制中具有较低层次的基础,不会受到语言特性的影响。然而,行为数据的感知准确性表现的显着差异表明,高级神经处理应该参与并为人类的跨语言学习体验提供至关重要的积极影响,从而影响学习结果。在本文中,我们研究了第二语言(L2)感知的效率与这种人类自愿注意的高级机制之间的关系。我们的发现通过对不同注意条件的准确性和反应时间进行测量,从而对现有统计模型的预测进行了修订。他们还建议,通过在人类认知过程中有效利用辅助注意模式,可以增强L2的学习和记忆能力。

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