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

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.