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The metamorphosis of the statistical segmentation output: lexicalization during artificial language learning.

机译:统计细分输出的变形:人工语言学习期间的词汇化。

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摘要

This study combined artificial language learning (ALL) with conventional experimental techniques to test whether statistical speech segmentation outputs are integrated into adult listeners' mental lexicon. Lexicalization was assessed through inhibitory effects of novel neighbors (created by the parsing process) on auditory lexical decisions to real words. Both immediately after familiarization and post-one week, ALL outputs were lexicalized only when the cues available during familiarization (transitional probabilities and wordlikeness) suggested the same parsing (Experiments 1 and 3). No lexicalization effect occurred with incongruent cues (Experiments 2 and 4). Yet, ALL differed from chance, suggesting a dissociation between item knowledge and lexicalization. Similarly contrasted results were found when frequency of occurrence of the stimuli was equated during familiarization (Experiments 3 and 4). Our findings thus indicate that ALL outputs may be lexicalized as far as the segmentation cues are congruent, and that this process cannot be accounted for by raw frequency.
机译:这项研究将人工语言学习(ALL)与常规实验技术相结合,以测试统计语音分段输出是否已整合到成人听众的心理词典中。通过新邻居(由解析过程创建)对听觉词汇决策对真实单词的抑制作用来评估词汇化。熟悉后和一周后都立即对所有输出进行词汇化,只有在熟悉过程中可用的线索(过渡概率和单词相似性)建议相同的解析时(实验1和3)。线索不一致时,没有词汇化作用发生(实验2和4)。但是,ALL与机会不同,这表明项目知识与词汇化之间是分离的。当熟悉过程中刺激的发生频率相等时,发现了类似的对比结果(实验3和4)。因此,我们的发现表明,只要分割线索完全一致,所有输出都可以词汇化,并且此过程无法用原始频率来解释。

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