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人工单词学习中的词汇切分:汇聚性次词汇线索的影响

Lexical Segmentation in Artificial Word Learning: The Effects of Converging Sublexical Cues.

作者信息

Bagou Odile, Frauenfelder Ulrich Hans

机构信息

University of Geneva, Switzerland.

出版信息

Lang Speech. 2018 Mar;61(1):3-30. doi: 10.1177/0023830917694664. Epub 2017 Mar 24.

DOI:10.1177/0023830917694664
PMID:29280405
Abstract

This study examines how French listeners segment and learn new words of artificial languages varying in the presence of different combinations of sublexical segmentation cues. The first experiment investigated the contribution of three different types of sublexical cues (acoustic-phonetic, phonological and prosodic cues) to word learning. The second experiment explored how participants specifically exploited sublexical prosodic cues. Whereas complementary cues signaling word-initial and word-final boundaries had synergistic effects on word learning in the first experiment, the two manipulated prosodic cues redundantly signaling word-final boundaries in the second experiment were rank-ordered with final pitch variations being more weighted than final lengthening. These results are discussed in light of the notions of cue type, cue position and cue efficiency.

摘要

本研究考察了法国听众如何对人工语言的新单词进行切分和学习,这些人工语言在存在不同组合的次词汇切分线索的情况下有所变化。第一个实验研究了三种不同类型的次词汇线索(声学语音、音系和韵律线索)对单词学习的贡献。第二个实验探究了参与者如何具体利用次词汇韵律线索。在第一个实验中,表明单词起始和单词结尾边界的互补线索对单词学习有协同作用,而在第二个实验中,两个被操纵的冗余信号单词结尾边界的韵律线索按等级排列,其中结尾音高变化比结尾延长更具权重。我们根据线索类型、线索位置和线索效率的概念对这些结果进行了讨论。

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