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Segmentability Differences Between Child-Directed and Adult-Directed Speech: A Systematic Test With an Ecologically Valid Corpus

机译:面向儿童和成人的语音之间的可分割性差异:具有生态有效语料库的系统测试

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摘要

Previous computational modeling suggests it is much easier to segment words from child-directed speech (CDS) than adult-directed speech (ADS). However, this conclusion is based on data collected in the laboratory, with CDS from play sessions and ADS between a parent and an experimenter, which may not be representative of ecologically collected CDS and ADS. Fully naturalistic ADS and CDS collected with a nonintrusive recording device as the child went about her day were analyzed with a diverse set of algorithms. The difference between registers was small compared to differences between algorithms; it reduced when corpora were matched, and it even reversed under some conditions. These results highlight the interest of studying learnability using naturalistic corpora and diverse algorithmic definitions.
机译:先前的计算模型表明,从儿童语音(CDS)分割单词比成人语音(ADS)容易得多。但是,该结论基于实验室收集的数据,以及来自父母和实验者之间的游戏会话中的CDS和ADS,这可能并不代表生态收集的CDS和ADS。在孩子成长的过程中,使用非侵入式记录设备收集的完全自然的ADS和CDS会通过多种算法进行分析。与算法之间的差异相比,寄存器之间的差异很小。当匹配语料库时,它减少了,甚至在某些条件下它反转了。这些结果突出了使用自然主义语料库和各种算法定义来研究可学习性的兴趣。

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