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Uncertainty Reduction as a Measure of Cognitive Load in Sentence Comprehension

机译:降低不确定性作为句子理解中认知负荷的量度

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The entropy-reduction hypothesis claims that the cognitive processing difficulty on a word in sentence context is determined by the word's effect on the uncertainty about the sentence. Here, this hypothesis is tested more thoroughly than has been done before, using a recurrent neural network for estimating entropy and self-paced reading for obtaining measures of cognitive processing load. Results show a positive relation between reading time on a word and the reduction in entropy due to processing that word, supporting the entropy-reduction hypothesis. Although this effect is independent from the effect of word surprisal, we find no evidence that these two measures correspond to cognitively distinct processes.
机译:熵减假设认为,句子上下文中单词的认知加工难度取决于单词对句子不确定性的影响。在这里,使用一种递归神经网络来估计熵和自定步伐的读数来获得对认知处理负荷的度量,从而比以前更彻底地检验了该假设。结果表明,单词阅读时间与因处理该单词而导致的熵减少之间存在正相关关系,这支持了熵减少假设。尽管此效果独立于单词惊奇的效果,但我们找不到证据表明这两种方法对应于认知上不同的过程。

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