To acquire language, infants must learn how to identify words and linguistic structure in speech. Statistical learning has been suggested to assist both of these tasks. However, infants' capacity to use statistics to discover words and structure together remains unclear. Further, it is not yet known how infants' statistical learning ability relates to their language development. We trained 17-month-old infants on an artificial language comprising non-adjacent dependencies, and examined their looking times on tasks assessing sensitivity to words and structure using an eye-tracked head-turn-preference paradigm. We measured infants' vocabulary size using a Communicative Development Inventory (CDI) concurrently and at 19, 21, 24, 25, 27, and 30 months to relate performance to language development. Infants could segment the words from speech, demonstrated by a significant difference in looking times to words versus part-words. Infants' segmentation performance was significantly related to their vocabulary size (receptive and expressive) both currently, and over time (receptive until 24 months, expressive until 30 months), but was not related to the rate of vocabulary growth. The data also suggest infants may have developed sensitivity to generalised structure, indicating similar statistical learning mechanisms may contribute to the discovery of words and structure in speech, but this was not related to vocabulary size.

中文翻译：

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婴儿期的非相邻依赖学习及其与语言发展的联系

为了获得语言，婴儿必须学习如何识别语音中的单词和语言结构。已经建议使用统计学习来协助这两项任务。然而，婴儿使用统计数据一起发现单词和结构的能力仍不清楚。此外，尚不清楚婴儿的统计学习能力如何与他们的语言发展相关。我们对 17 个月大的婴儿进行了包含非相邻依赖性的人工语言的训练，并使用眼动追踪头部转向偏好范式检查了他们在评估对单词和结构的敏感性的任务中的观看时间。我们同时在 19、21、24、25、27 和 30 个月时使用交流发展量表 (CDI) 测量婴儿的词汇量，以将表现与语言发展联系起来。婴儿可以从语音中分割出单词，这可以通过查看单词与部分单词的显着差异来证明。婴儿的切分表现与他们当前和随着时间的推移（接受到 24 个月，表达到 30 个月）的词汇量（接受和表达）显着相关，但与词汇增长速度无关。数据还表明婴儿可能对广义结构产生了敏感性，表明类似的统计学习机制可能有助于发现语音中的单词和结构，但这与词汇量大小无关。并且随着时间的推移（接受到 24 个月，表达到 30 个月），但与词汇增长速度无关。数据还表明婴儿可能对广义结构产生了敏感性，表明类似的统计学习机制可能有助于发现语音中的单词和结构，但这与词汇量大小无关。并且随着时间的推移（接受到 24 个月，表达到 30 个月），但与词汇增长速度无关。数据还表明婴儿可能对广义结构产生了敏感性，表明类似的统计学习机制可能有助于发现语音中的单词和结构，但这与词汇量大小无关。