Arizona State University, Tempe, AZ, USA.
Duke University, Durham, NC, USA.
Dev Sci. 2020 Mar;23(2):e12896. doi: 10.1111/desc.12896. Epub 2019 Sep 9.
Language acquisition depends on the ability to detect and track the distributional properties of speech. Successful acquisition also necessitates detecting changes in those properties, which can occur when the learner encounters different speakers, topics, dialects, or languages. When encountering multiple speech streams with different underlying statistics but overlapping features, how do infants keep track of the properties of each speech stream separately? In four experiments, we tested whether 8-month-old monolingual infants (N = 144) can track the underlying statistics of two artificial speech streams that share a portion of their syllables. We first presented each stream individually. We then presented the two speech streams in sequence, without contextual cues signaling the different speech streams, and subsequently added pitch and accent cues to help learners track each stream separately. The results reveal that monolingual infants experience difficulty tracking the statistical regularities in two speech streams presented sequentially, even when provided with contextual cues intended to facilitate separation of the speech streams. We discuss the implications of our findings for understanding how infants learn and separate the input when confronted with multiple statistical structures.
语言习得依赖于检测和跟踪语音分布特征的能力。成功的习得还需要检测这些特征的变化，而这些变化可能发生在学习者遇到不同的说话者、话题、方言或语言时。当遇到具有不同潜在统计数据但重叠特征的多个语音流时，婴儿如何分别跟踪每个语音流的属性？在四项实验中，我们测试了 8 个月大的单语婴儿（N=144）是否能够跟踪两个共享部分音节的人工语音流的潜在统计数据。我们首先单独呈现每个流。然后，我们在没有上下文线索表明不同语音流的情况下按顺序呈现两个语音流，随后添加音高和重音线索，以帮助学习者分别跟踪每个流。结果表明，即使提供了旨在促进语音流分离的上下文线索，单语婴儿在按顺序呈现两个语音流时也难以跟踪其统计规律。我们讨论了我们的发现对理解婴儿在面对多个统计结构时如何学习和分离输入的意义。
