研究儿童的身体和语言环境之间的关系:谁在和谁说话,在哪里说话?

A. Sangwan, J. Hansen, Dwight W. Irvin, S. Crutchfield, C. Greenwood
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引用次数: 18

摘要

了解早期学习者的语言环境是促进学校成功的关键。越来越多的大型项目(例如,普罗维登斯谈话,弥合单词差距)正在调查幼儿的语言环境,试图更好地理解和促进语言的习得和发展。用于收集和分析与年轻学习者语言环境有关的数据的主要工具是LENA数字语言处理器(DLP)。LENA允许连续捕捉语言,主要集中在一个孩子与成人的互动长达16小时。随后使用口语技术(SLT)对音频进行分析,提供了有意义的指标,如成人总字数和会话次数。单独收集连续音频的一个缺点是失去了成人对儿童或儿童对儿童交流的物理背景。在这项研究中,我们描述了我们最近的数据收集工作,它结合了LENA和Ubisense传感器,允许同时捕获空间信息以及语音和时间。我们对研究儿童的身体环境和语言环境之间的关系特别感兴趣。在本研究中,我们描述了我们的收集方法、最初探针实验的结果以及我们在开发相关SLT指标方面的最新努力。本研究中描述的新数据和技术可以帮助我们更深入地了解物理环境如何促进或鼓励幼儿课堂中的交流。从理论上讲,这种语音和定位技术可以为未来的学习空间的设计做出贡献,这些空间是专门为正常发育的儿童或有残疾或有残疾风险的儿童设计的。
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Studying the relationship between physical and language environments of children: Who's speaking to whom and where?
Understanding the language environments of early learners is critical in facilitating school success. Increasingly large scale projects (e.g., Providence Talks, Bridging the Word Gap) are investigating the language environments of young children in an attempt to better understand and facilitate language acquisition and development. The primary tool used to collect and analyze data related to the language environments of young learners is the LENA digital language processor (DLP). LENA allows for the continuous capture of language, primarily focused on a single child to adult interactions for up to 16 hrs. Subsequent analysis of the audio using spoken language technology (SLT) provides meaningful metrics such as total adult word count and conversational turns. One shortcoming of collecting continuous audio alone is that the physical context of adult-to-child or child-to-child communication is lost. In this study, we describe our recent data collection effort which combines the LENA and Ubisense sensors to allow for simultaneous capture of both spacial information along with speech and time. We are particularly interested in researching the relationship between the physical and language environments of children. In this study, we describe our collection methodology, results from initial probe experiments and our latest efforts in developing relevant SLT metrics. The new data and techniques described in this study can help in developing a richer understanding of how physical environments promote or encourage communication in early childhood classrooms. In theory, such speech and location technology can contribute to the design of future learning spaces specifically designed for typically developing children, or those with or at-risk for disabilities.
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