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: 2235363
• 负责人: Michael Jones
• 金额: $ 11.08万
• 依托单位: Indiana University
• 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=2235363&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 will help 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 will ultimately inform 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 will test 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 be able to 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（有时称为我们的心理词典）中搜索正确的单词是人类经常做的事情，而且大多数情况下都非常轻松。目前的研究旨在更好地理解单词记忆搜索的机制，这将帮助我们更好地理解单词在大脑中是如何组织和检索的。此外，这种搜索过程的失败，表现为找词困难或舌尖上有单词，可能是某些临床疾病的症状，而关于这种记忆搜索如何工作的更强有力的理论可以帮助我们理解为什么它有时会失败。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。单词搜索是在记忆系统中概念化的，其中包括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头）。这项研究最终将为记忆搜索的临床测量的使用和解释提供信息，并促进一般 STEM 和认知科学中代表性不足的身份的参与。这项合作提案汇集了心理语言学、网络科学和语言建模领域的研究人员，以开发一个统一的模型使用在基础科学和临床环境中广泛使用的任务（流畅性任务）来研究词汇搜索和检索的计算框架。在此任务中，参与者被要求在一定时间内说出尽可能多的符合某个类别（例如动物类型）的单词。拟议的工作将测试一个中心假设，即记忆搜索是通过不同信息源之间的复杂相互作用以及基于我们在世界上独特经历的个体差异而展开的。我们的方法包括设计一个游戏化的、基于网络的流畅性实验，以生成一个大型的言语流畅性行为数据集，并使用基于两种基本搜索机制（最佳觅食和随机游走）的新颖计算方法来解释哪些单词按什么顺序产生。通过这种方法，我们将能够评估意义和声音信息的相互作用，并解释不同个体在执行这些任务时观察到的差异。所提出的基于网络的游戏化流畅性任务，与理论驱动、自下而上的知识表示和记忆搜索计算模型相结合，有可能生成前所未有的流畅性数据量，揭示有关记忆搜索的新颖见解，并开辟新路线跨心理学和语言学领域的探究，从而产生了更强大和统一的记忆搜索认知理论。该项目由感知、行动和认知计划以及刺激竞争研究既定计划 (EPSCoR) 联合资助。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。