The surprising power of statistical learning: When fragment knowledge leads to false memories of unheard words
The surprising power of statistical learning: When fragment knowledge leads to false memories of unheard words
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DOI：
10.1016/j.jml.2008.10.003
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发表时间：
2009-04-01
影响因子：
4.3
通讯作者：
Mehler, Jacques
中科院分区：
文献类型：
--
作者：
Endress, Ansgar D.;Mehler, Jacques
分词，即从流利的语音中提取单词，是语言学习者必须掌握的首要问题之一。人们普遍认为，统计过程，特别是那些跟踪“过渡概率”(TPS)的过程，对于分词是重要的。然而，有证据表明，单词形式的存储格式不同于可以从TPS构建的存储格式，即在单词中音素和音节的位置方面。与这一观点一致，我们发现，如果幻词和出现的词具有相同的统计结构，那么基于TP的过程并不会让学习者更熟悉被听到600次的项目，而不是完全没有听到的幻词。此外，与频繁的音节组合相比，受试者更熟悉虚词。相比之下，最小的韵律类感知线索可以让学习者识别实际的项目。TPS可以很好地发出共现音节的信号；然而，这似乎不会导致提取类似单词的单位。我们回顾了词边界的其他线索，特别是韵律线索，这些线索可能允许在不需要特定语言知识的情况下构建位置记忆，并建议需要重新评估它们对分词的贡献。(C)2008 Elsevier Inc.保留所有权利。
Word-segmentation, that is, the extraction of words from fluent speech, is one of the first problems language learners have to master. It is generally believed that statistical processes, in particular those tracking "transitional probabilities" (TPs), are important to word-segmentation. However, there is evidence that word forms are stored in memory formats differing from those that can be constructed from TPs, i.e. in terms of the positions of phonemes and syllables within words. In line with this view, we show that TP-based processes leave learners no more familiar with items heard 600 times than with "phantom-words" not heard at all if the phantom-words have the same statistical structure as the occurring items. Moreover, participants are more familiar with phantom-words than with frequent syllable combinations. In contrast, minimal prosody-like perceptual cues allow learners to recognize actual items. TPs may well signal co-occurring syllables; this, however, does not seem to lead to the extraction of word-like units. We review other, in particular prosodic, cues to word-boundaries which may allow the construction of positional memories while not requiring language-specific knowledge, and suggest that their contributions to word-segmentation need to be reassessed. (C) 2008 Elsevier Inc. All rights reserved.