Word meaning and sentence comprehension

词义和句子理解

• 批准号: 155704-2007
• 负责人: McRae, Kenneth
• 金额: $ 1.9万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2010
• 资助国家: 加拿大
• 起止时间: 2010-01-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=452106
• 关键词: Word; meaning; sentence; comprehension

Language is a major part of what makes us human. The broad objective of my research is to understand how people interpret what they hear and read, how this knowledge develops in children, and how it becomes degraded due to brain impairments. My research is roughly divided into two parts. In one part, I and my collaborators study people's memory for the meaning of words that refer to living things such as dog, and nonliving things such as toaster. To do this, we use "neural networks", which are models of mental processing that are written as computer programs. We have built a series of neural networks that produce the meaning of words like toaster given how the word is spelled or pronounced. We study how our models work and then use that knowledge to come up with predictions that we test on human participants. This testing typically involves looking at the time it takes for people to answer questions like, "Does a shirt have a pocket?" or "Does the word dog refer to something you can touch?" We also damage our models by altering the program so that part of the simulated mind no longer works correctly. We then test whether the damaged model mimics the performance of people who have suffered brain damage.

语言是我们人类的重要组成部分。我研究的主要目标是了解人们如何解释他们所听到和读到的内容，这些知识如何在儿童中发展，以及这些知识如何因大脑损伤而退化。我的研究大致分为两部分。在其中一部分中，我和我的合作者研究了人们对涉及生物（例如狗）和非生物（例如烤面包机）的单词含义的记忆。为此，我们使用“神经网络”，它是编写为计算机程序的心理处理模型。我们建立了一系列神经网络，根据单词的拼写或发音，可以生成诸如烤面包机之类的单词的含义。我们研究模型的工作原理，然后利用这些知识提出预测，并在人类参与者身上进行测试。此测试通常涉及查看人们回答“衬衫有口袋吗？”等问题所需的时间。或者“狗这个词是指你可以触摸的东西吗？”我们还通过改变程序来损坏我们的模型，使部分模拟思维不再正常工作。然后我们测试受损模型是否模仿脑损伤患者的表现。