Word meaning and sentence comprehension

词义和句子理解

• 批准号: 155704-2007
• 负责人: McRae, Ken
• 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: 2011
• 资助国家: 加拿大
• 起止时间: 2011-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=476092
• 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.

语言是我们成为人类的重要组成部分。我的研究的广泛目标是了解人们如何解释他们所听到和阅读的内容，这些知识如何在儿童中发展，以及如何由于大脑损伤而退化。我的研究大致分为两个部分。在一部分中，我和我的合作者研究了人们对单词含义的记忆，这些单词指的是像狗这样的生物，以及像烤面包机这样的非生物。为了做到这一点，我们使用“神经网络”，这是一种以计算机程序形式编写的心理处理模型。我们已经建立了一系列神经网络，根据单词的拼写或发音来产生单词的含义。我们研究我们的模型是如何工作的，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。这种测试通常包括观察人们回答问题所需的时间，比如“衬衫有口袋吗？或者“狗这个词是指你可以摸到的东西吗？”“我们还通过改变程序来破坏我们的模型，使模拟思维的一部分不再正确工作。然后，我们测试受损模型是否模仿了遭受脑损伤的人的表现。