True and false recognition in MINERVA 2: Extension to sentences and metaphors

IF 2.9 1区 心理学 Q1 LINGUISTICS
J. Nick Reid, Randall K. Jamieson
{"title":"True and false recognition in MINERVA 2: Extension to sentences and metaphors","authors":"J. Nick Reid,&nbsp;Randall K. Jamieson","doi":"10.1016/j.jml.2022.104397","DOIUrl":null,"url":null,"abstract":"<div><p>Arndt and Hirshman (1998) used MINERVA 2 to simulate true and false recognition in DRM-style lists and found that the model was able to capture many features of the empirical data. Here, we first replicate their simulations, but using empirically structured vectors derived from Latent Semantic Analysis rather than the randomly generated vectors characteristic of MINERVA 2. We report that the model still captures the DRM effect with fewer free parameters. We then extend our analyses to true and false recognition for full sentences and metaphorical expressions. Using a simple bag-of-words representation for sentences, we find that the MINERVA 2 model captures classic sentence false recognition findings from Bransford and Frank (1971) and a more recent finding from Reid and Katz (2018a) that demonstrates false recognition of unstudied sentences that share a metaphorical but not literal theme to studied sentences. These simulations provide evidence that an instance-based memory model, when amalgamated with structured semantic representations from a distributional semantic model, can account for true and false recognition across different types of language experiences.</p></div>","PeriodicalId":16493,"journal":{"name":"Journal of memory and language","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of memory and language","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0749596X22000845","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"LINGUISTICS","Score":null,"Total":0}
引用次数: 4

Abstract

Arndt and Hirshman (1998) used MINERVA 2 to simulate true and false recognition in DRM-style lists and found that the model was able to capture many features of the empirical data. Here, we first replicate their simulations, but using empirically structured vectors derived from Latent Semantic Analysis rather than the randomly generated vectors characteristic of MINERVA 2. We report that the model still captures the DRM effect with fewer free parameters. We then extend our analyses to true and false recognition for full sentences and metaphorical expressions. Using a simple bag-of-words representation for sentences, we find that the MINERVA 2 model captures classic sentence false recognition findings from Bransford and Frank (1971) and a more recent finding from Reid and Katz (2018a) that demonstrates false recognition of unstudied sentences that share a metaphorical but not literal theme to studied sentences. These simulations provide evidence that an instance-based memory model, when amalgamated with structured semantic representations from a distributional semantic model, can account for true and false recognition across different types of language experiences.

MINERVA 2中的真与假识别:对句子和隐喻的扩展
Arndt和Hirshman(1998)使用MINERVA 2模拟了drm风格列表中的真假识别,发现该模型能够捕捉到经验数据的许多特征。在这里,我们首先复制了他们的模拟,但使用的是来自潜在语义分析的经验结构向量,而不是MINERVA 2中随机生成的向量。我们报告了该模型在自由参数较少的情况下仍然捕获DRM效应。然后,我们将分析扩展到对完整句子和隐喻表达的真假识别。使用简单的句子词袋表示,我们发现MINERVA 2模型捕获了Bransford和Frank(1971)的经典句子错误识别发现,以及Reid和Katz (2018a)的最新发现,该发现表明对未研究的句子的错误识别,这些句子与研究的句子共享隐喻而不是字面主题。这些模拟提供的证据表明,当基于实例的记忆模型与来自分布语义模型的结构化语义表示相结合时,可以在不同类型的语言经验中解释真假识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
8.70
自引率
14.00%
发文量
49
审稿时长
12.7 weeks
期刊介绍: Articles in the Journal of Memory and Language contribute to the formulation of scientific issues and theories in the areas of memory, language comprehension and production, and cognitive processes. Special emphasis is given to research articles that provide new theoretical insights based on a carefully laid empirical foundation. The journal generally favors articles that provide multiple experiments. In addition, significant theoretical papers without new experimental findings may be published. The Journal of Memory and Language is a valuable tool for cognitive scientists, including psychologists, linguists, and others interested in memory and learning, language, reading, and speech. Research Areas include: • Topics that illuminate aspects of memory or language processing • Linguistics • Neuropsychology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信