Collaborative Research: CompCog: Modeling Search within the Mental Lexicon

合作研究：CompCog：心理词典中的建模搜索

• 批准号: 2235362
• 负责人: Abhilasha Kumar
• 金额: $ 44.88万
• 依托单位: Bowdoin College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2235362&HistoricalAwards=false
• 关键词: Collaborative; Research; CompCog; Modeling; Search

Searching for the right word in our mental dictionary - sometimes called our mental lexicon - is something that humans do frequently and mostly with great ease. The current research is designed to better understand the mechanisms that underlie memory search for words, which helps us better understand how words are organized and retrieved in the mind. Furthermore, failures of this search process, which show up as word-finding difficulties or having words on the tip of your tongue, can be symptomatic of certain clinical disorders, and a stronger theory of how this kind of memory search works can inform our understanding of why it sometimes fails. The proposed research leverages recent advances in machine learning, network science, and gamification. Word search is conceptualized within a memory system that includes both information about a word's meaning (e.g. that a dog is a type of animal) and information about a word's sounds (e.g., that dog and dot start with the same sounds). This research informs the use and interpretation of clinical measures of memory search as well as promote participation from underrepresented identities in STEM generally and cognitive science specifically.This collaborative proposal brings together researchers in psycholinguistics, network science, and language modeling to develop a unified computational framework to study lexical search and retrieval using a task that is widely used in both basic science and clinical settings: the fluency task. In this task, participants are asked to name as many words as they can in a certain amount of time that all fit with a category (e.g. types of animals). The proposed work tests the central hypothesis that memory search unfolds via complex interactions between different sources of information as well as individual variation based on our unique experiences in the world. Our approach involves designing a gamified, web-based fluency experiment to generate a large behavioral dataset of verbal fluency and using novel computational approaches based on two fundamental search mechanisms (optimal foraging and random walks) to account for which words are produced in what order. With this approach, we will evaluate the interaction of meaning and sound information, and account for the variance observed in how different individuals perform on these tasks. The proposed gamified web-based fluency task, combined with theory-driven, bottom-up computational models of knowledge representation and memory search have the potential to generate an unprecedented amount of fluency data, uncover novel insights about memory search, and open up new lines of inquiry that cut across fields of psychology and linguistics, thereby leading to a more robust and unified cognitive theory of memory search. This project is jointly funded by the Perception, Action and Cognition program and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在我们的心理词典中搜索正确的单词 - 有时称为我们的精神词典 - 是人类经常且大部分轻松地做的事情。当前的研究旨在更好地理解记忆搜索单词的基础的机制，这有助于我们更好地理解单词在思想中的组织和检索。此外，这种搜索过程的失败表现为单词发现困难或舌尖上有单词，可能是某些临床疾病的征兆，并且对这种记忆搜索的工作方式的更强大理论可以使我们对为什么有时会失败的理解来了解我们的理解。拟议的研究利用了机器学习，网络科学和游戏化的最新进展。单词搜索是在存储系统中概念化的，该存储系统既包含有关单词含义的信息（例如，狗是一种动物）和有关单词声音的信息（例如，狗和点以相同的声音开始）。这项研究为记忆搜索的临床措施的使用和解释提供了信息，并促进了总体上代表性不足的身份的参与，并具体促进了认知科学的参与。该协作提案将心理语言学，网络科学和语言模型的研究人员汇集在一起​​，以开发统一的计算框架来研究词汇搜索和检索，以研究词汇搜索和检索，从而在两种临床上进行了临床和临床的临床范围，该工作均已进行了临床。在此任务中，要求参与者在一定时间内列举尽可能多的单词（例如动物类型）。拟议的工作检验了一个中心假设，即记忆搜索通过不同信息来源之间的复杂相互作用以及基于我们在世界上独特的经验而进行的复杂相互作用。我们的方法涉及设计一个基于游戏的，基于网络的流利性实验，以生成大量的言语流利性行为数据集，并使用基于两种基本搜索机制（最佳觅食和随机步行）的新型计算方法来说明以什么顺序产生单词。通过这种方法，我们将评估含义和声音信息的相互作用，并说明在不同个体对这些任务的执行方式中观察到的差异。拟议的基于GAM的基于GAM的流利任务，再加上理论驱动的自下而上的知识表示和记忆搜索的计算模型，有可能生成前所未有的流利性数据，发现有关记忆搜索的新颖见解，并打开了新的询问线，从而削减了跨心理学和语言的领域，从而导致了更强大的稳固和统一的记忆理论，以实现跨越强大的探索。该项目由感知，行动和认知计划以及刺激竞争性研究的既定计划共同资助。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响来通过评估来支持的。