EARLY WORD LEARNING--COMPUTATIONAL AND BEHAVIORAL TESTS

描述(申请人摘要)：孩子们是令人惊叹的单词学习者。 尽管每个新词的可能含义的数量是巨大的， 孩子们学习单词的速度很快，而且似乎不费什么力气。上一首 研究表明，孩子们有偏见地只考虑其中的一些 生词的可能含义。然而，单词学习的起源 偏差及其在时刻基础上的运作机制 尚未确定。拟议的项目解决了我们在 对单词学习的理解。在三个项目中，我将测试 假设词汇学习偏差源于统计规律 在语言和类别方面，孩子们学到了。具体问题 讨论如下：(1)语言中的统计规律是什么 儿童的输入；(2)可以简单地学习统计规律 复制特定单词学习偏见的发展；以及(3)如果 在儿童知道的单词中发现的统计规则被改变了，是吗？ 特定词汇学习因变化而产生偏向的发展轨迹？ 这些问题在神经网络模拟中得到了解决 特定词汇学习偏向的发展；实验研究 单词学习偏见的自然发展是通过教学来改变的 儿童单词；以及单词学习变化的模型 从词汇训练中脱身。

DESCRIPTION (Applicant's Abstract): Children are amazing word learners. Even though the number of possible meanings for each novel word is immense, children learn words quickly and with seemingly little effort. Previous research has suggested that children are biased to only consider some of the possible meanings for a new word. However, the origin of word learning biases and the mechanisms by which they operate on a moment-to-moment basis has yet to be determined. The proposed project addresses this gap in our understanding of word learning. In three projects, I will test the hypothesis that word learning biases develop out of statistical regularities in the language and categories children learn. The specific questions addressed are: (1) what are the statistical regularities in the language input of children; (2) can a simple learner of statistical regularities replicate the development of specific word-learning biases; and (3) if the statistical regularities found in the words children know are altered, does the developmental trajectory of specific word learning biases by change? These questions are addressed in neural network simulations of the development of specific word learning biases; experimental studies in which the natural development of a word learning bias is altered by teaching children words; and in modeling of the changes in word learning that arise from the lexical training.