Continuous measure of word learning supports associative model
Continuous measure of word learning supports associative model
复制标题
单词学习的连续测量支持关联模型
DOI：
--
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Chen Yu
中科院分区：
文献类型：
--
作者：
George Kachergis;Chen Yu
跨情景学习，即在由多个单词和指代物组成的多个场景中学习单词含义的能力，被认为是语言习得的重要工具。这种能力已经在婴儿、儿童和成人中进行了研究，但关于跨情景单词学习过程中的基本存储和检索机制仍有很多争论。很难揭示学习机制，部分原因是标准的实验范式，在一系列的训练试验中，每次只提供几个单词和物体，只在训练结束时，在每个单词和物体对出现几次之后，才测量学习情况。因此，确切的学习时刻及其当前和历史背景无法直接调查。这篇论文提供了一个跨情境学习任务的版本，在这个任务中，每次听到一个单词都会做出一个反应，在最后的测试中也是如此。我们将其与典型的跨情境学习任务进行比较，并检查反应分布与两种最新的单词学习计算模型的匹配程度。
Cross-situational learning, the ability to learn word meanings across multiple scenes consisting of multiple words and referents, is thought to be an important tool for language acquisition. The ability has been studied in infants, children, and adults, and yet there is much debate about the basic storage and retrieval mechanisms that operate during cross-situational word learning. It has been difficult to uncover the learning mechanics in part because the standard experimental paradigm, which presents a few words and objects on each of a series of training trials, measures learning only at the end of training after several occurrences of each word-object pair. Thus, the exact learning moment-and its current and historical context-cannot be investigated directly. This paper offers a version of the cross-situational learning task in which a response is made each time a word is heard, as well as in a final test. We compare this to the typical cross-situational learning task, and examine how well the response distributions match two recent computational models of word learning.
在跨情境单词学习过程中观察和建模发展知识和不确定性。
DOI：
10.1109/tcds.2017.2735540
发表时间：
2018
影响因子：
5
作者：
Kachergis,George;Yu,Chen
通讯作者：
Yu,Chen
影响因子：
56.9
作者：
Berns, GS;Cohen, JD;Mintun, MA
通讯作者：
Mintun, MA