RUI: Computational Developmental Bilingualism: A Self-Organizing Model of Bilingual Lexical Acquisition

RUI：计算发展双语：双语词汇习得的自组织模型

• 批准号: 0642586
• 负责人: Craig Kinsley
• 金额: --
• 依托单位: University of Richmond
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0642586&HistoricalAwards=false
• 关键词: RUI; Computational; Developmental; Bilingualism; Self

The ability of children to acquire their native vocabulary with such ease is truly remarkable, and one that we are only beginning to understand scientifically. In this light it is even more remarkable how easily children raised in bilingual environments can learn two different vocabularies. How are their language systems developed and organized to cope with two different sets of mental dictionaries? Cognitive scientists have addressed this question by studying the language behaviors of bilinguals through their course of development and into adulthood, and in their social and cultural contexts. They have even begun to examine the neural bases of bilingualism, but one approach that has not received much attention is the use of computational models. Meteorologists, for instance, use computational models of weather systems like hurricanes and tornadoes, not just to predict their occurrence, but to more basically understand their dynamics and underlying mechanisms. Likewise, models of cognitive systems have a rich tradition of making progress in many areas of cognitive science, yet to date, bilingualism is not one of them.With support of the National Science Foundation, Dr. Li is developing a large-scale computational model of bilingual vocabulary development. The modeling efforts are based on self-organizing connectionist networks that have been used previously in a number of areas of language research, including vocabulary development in monolingual children. Such self-organizing models are well-suited to questions of learning and development, in that these questions are naturally cast in terms of balancing competitive and cooperative interactions among system components. In the case of bilingual vocabulary development, the components can be construed as individual words from the languages being learned. By modeling vocabulary development in this way, Dr. Li is investigating how language learning is a fundamentally incremental process whereby bilingual knowledge and skills learned later in life build upon earlier language learning. This point has important implications for bilingual education, and the debilitating effects that brain trauma or disease can have on bilingual language processing.

孩子们如此轻松地掌握母语词汇的能力确实令人惊叹，而我们才刚刚开始科学地理解这一能力。 从这个角度来看，在双语环境中长大的孩子能够轻松地学习两种不同的词汇就更值得注意了。 他们的语言系统是如何发展和组织来应对两套不同的心理词典的？ 认知科学家通过研究双语者从成长过程到成年以及社会和文化背景下的语言行为来解决这个问题。 他们甚至开始研究双语的神经基础，但一种没有受到太多关注的方法是使用计算模型。 例如，气象学家使用飓风和龙卷风等天气系统的计算模型，不仅是为了预测它们的发生，而且是为了更基本地了解它们的动态和潜在机制。 同样，认知系统模型在认知科学的许多领域都有取得进展的丰富传统，但迄今为止，双语并不是其中之一。在美国国家科学基金会的支持下，李博士正在开发一种双语词汇发展的大规模计算模型。 建模工作基于自组织联结网络，该网络之前已用于许多语言研究领域，包括单语儿童的词汇发展。 这种自组织模型非常适合学习和发展问题，因为这些问题自然地涉及平衡系统组件之间的竞争和合作交互。 在双语词汇发展的情况下，这些成分可以被解释为来自正在学习的语言的单个单词。 通过以这种方式模拟词汇发展，李博士正在研究语言学习如何从根本上是一个渐进的过程，即以后学习的双语知识和技能建立在早期语言学习的基础上。 这一点对双语教育以及脑外伤或疾病对双语语言处理造成的破坏性影响具有重要意义。