Lexical knowledge boosts statistically-driven speech segmentation.
Lexical knowledge boosts statistically-driven speech segmentation.
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DOI：
10.1037/xlm0000567
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发表时间：
2019-01
期刊：
影响因子：
--
通讯作者：
Mattys SL
中科院分区：
文献类型：
--
作者：
Palmer SD;Hutson J;White L;Mattys SL
已知单词可以作为发现连接语音中的新词的锚的假设得到了计算和经验上的支持。然而，关于已知单词的自举效应如何与其他词汇习得机制，如统计学习相互作用的证据还不完整。在三个实验中，我们研究了在人工语言中引入一个已知单词的后果，除了交叉音节转移概率外，没有切分线索。我们从一种包含4个三音节新词的人工语言开始，并在随后的再认记忆任务中观察了标准的高于机会的表现。然后我们将4个新词中的1个替换为一个真实的词(明天)，并注意到其他3个新词的切分得到了改进。当真实单词的长度与小说中的单词(哲学)的长度不同时，这种改进得以保持，从而排除了基于度量预期的解释。当将该词添加到4个原始小说单词中而不是替换其中1个时，也保持了改进。总而言之，这些结果表明，在原本没有意义的数据流中，已知词充当了发现新词的锚。在解释结果时，我们对比了一种机制，即词汇增加仅仅是注意到已知词的边缘的结果，而另一种机制是，已知词更普遍地增强了对过渡概率的敏感性。
The hypothesis that known words can serve as anchors for discovering new words in connected speech has computational and empirical support. However, evidence for how the bootstrapping effect of known words interacts with other mechanisms of lexical acquisition, such as statistical learning, is incomplete. In 3 experiments, we investigated the consequences of introducing a known word in an artificial language with no segmentation cues other than cross-syllable transitional probabilities. We started with an artificial language containing 4 trisyllabic novel words and observed standard above-chance performance in a subsequent recognition memory task. We then replaced 1 of the 4 novel words with a real word (tomorrow) and noted improved segmentation of the other 3 novel words. This improvement was maintained when the real word was a different length to the novel words (philosophy), ruling out an explanation based on metrical expectation. The improvement was also maintained when the word was added to the 4 original novel words rather than replacing 1 of them. Together, these results show that known words in an otherwise meaningless stream serve as anchors for discovering new words. In interpreting the results, we contrast a mechanism where the lexical boost is merely the consequence of attending to the edges of known words, with a mechanism where known words enhance sensitivity to transitional probabilities more generally.
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影响因子：
2.6
作者：
Cunillera, Toni;Laine, Matti;Rodriguez-Fornells, Antoni
通讯作者：
Rodriguez-Fornells, Antoni
影响因子：
2.5
作者：
NEWPORT, EL
通讯作者：
NEWPORT, EL
DOI：
10.3758/bf03195503
发表时间：
2003-02-01
期刊：
BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS
影响因子：
--
作者：
Forster, KI;Forster, JC
通讯作者：
Forster, JC
影响因子：
2.6
作者：
MCCLELLAND, JL;ELMAN, JL
通讯作者：
ELMAN, JL
影响因子：
3.4
作者：
NORRIS, D
通讯作者：
NORRIS, D