Doctoral Dissertation Research: Empirical Studies and Probabilistic Models of Word Segmentation and Word Learning

博士论文研究：分词和单词学习的实证研究和概率模型

• 批准号: 0746251
• 负责人: Edward Gibson
• 金额: $ 1.18万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-02-01 至 2010-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0746251&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Empirical; Studies

How do children learn their first words? To learn even a simple word like "table," a child must first pick out that word, rather than, for example, the non-word "the-tay," from the continuous string of syllables comprising a sentence like "it's under the table." The child must also learn that the word "table" refers to one particular object (a table), rather than any of the other things present at the time the word was used (a chair, the family dog, etc.). Recent research suggests that children make use of the statistical distribution of phonemes to solve first problem, word segmentation, and similarly make use of the co-occurrence statistics of words and objects to solve the second problem, word-world mapping.Graduate student Michael Frank, under the guidance of Dr. Edward Gibson, will use computational methods to help to characterize the nature of the learning mechanisms involved in these tasks. This grant will support studies with adults at MIT and a collaboration with Dr. Anne Fernald at Stanford University to conduct experiments with infants and young children. The goal of these experiments is to vary natural parameters in the learning situation using simple artificial languages to find out what makes learning harder or easier. Computational models will be evaluated on their fit to these data. This project will both contribute to our understanding of how children acquire the first words of their language and provide new directions for computer scientists attempting to create natural language processing systems.

孩子们是如何学会他们的第一个单词的？要学习哪怕是一个简单的单词，比如“table”，孩子首先必须从组成一个句子的连续音节串中挑出这个单词，而不是非单词“the-tay”，比如“it's under the table”。孩子还必须学会“桌子”这个词指的是一个特定的物体（桌子），而不是使用这个词时出现的任何其他东西（椅子，家里的狗等）。最近的研究表明，儿童利用音素的统计分布来解决第一个问题，分词，同样地，利用词和物体的共现统计来解决第二个问题，词世界映射。研究生迈克尔弗兰克，在爱德华吉布森博士的指导下，将使用计算方法来帮助描述这些任务中涉及的学习机制的性质。这笔赠款将支持麻省理工学院的成人研究，以及与斯坦福大学的Anne Fernald博士合作，在婴儿和幼儿身上进行实验。这些实验的目的是使用简单的人工语言改变学习环境中的自然参数，以找出是什么让学习更难或更容易。将评价计算模型与这些数据的拟合情况。该项目将有助于我们理解儿童如何获得他们语言的第一个单词，并为试图创建自然语言处理系统的计算机科学家提供新的方向。