Infant learning of acoustic cues to word boundaries

描述（由申请人提供）：婴儿能够利用许多线索，包括语音信息，如单词重音，在流利的言语中定位单词边界。本应用程序提出的研究旨在揭示对声音线索的注意的发展过程，以及允许婴儿发现他们听到的语音中的声音事件所表示的单词边界的学习机制。我们假设婴儿使用统计学习——通过跟踪输入的协方差模式来发现规律的过程——来初步识别流利言语中的单词边界，然后检测早期词汇中单词开始和偏移的声学规律。如果是这样的话，只要婴儿能够从这种语言中提取单词，他们就应该能够发现与新语言的单词边界相对应的声学规律。此外，他们应该能够学习哪些声学事件指示单词边界，不仅从完美的关联中，而且从协方差中，这是通常存在于自然语言中的协方差类型。本研究将为婴儿习得与单词边界相关的多种声学规律提供一个模型。

DESCRIPTION (provided by applicant): Infants are capable of exploiting many cues, including acoustic information such as word stress, to locate word boundaries in fluent speech. The research proposed in this application is designed to uncover the developmental course of attention to acoustic cues, and the learning mechanisms that allow infants to discover what the acoustic events in the speech they hear signify about word boundaries. We hypothesize that infants use statistical learning - the process of discovering regularities by tracking patterns of covariance in the input - to initially identify word boundaries in fluent speech, then detect the acoustic regularities of the word onsets and offsets in their early vocabulary. If so, infants should be able to detect the acoustic regularities that correspond to word boundaries in novel languages, so long as they are able to extract words from such a language. Further, they should be able to learn which acoustic events indicate word boundaries not just from perfect associations, but from covariances that occur only a majority of the time, which is the type of covariance usually present in natural languages. This research will provide a model for infant acquisition of multiple acoustic regularities associated with word boundaries.