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.

在我们的心理词典中搜索正确的单词-有时被称为我们的心理词典-是人类经常做的事情，而且大多数情况下非常容易。目前的研究旨在更好地理解记忆搜索单词的机制，这将有助于我们更好地理解单词是如何在大脑中组织和检索的。此外，这种搜索过程的失败，表现为找词困难或有话要说，可能是某些临床疾病的症状，这种记忆搜索如何工作的更强大的理论可以告诉我们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。单词搜索在记忆系统中被概念化，该记忆系统包括关于单词的含义的信息（例如，狗是一种动物）和关于单词的声音的信息（例如，that dog和dot以相同的声音开始）。这项研究最终将为记忆搜索的临床措施的使用和解释提供信息，并促进STEM中代表性不足的身份的参与，特别是认知科学。这项合作提案汇集了心理语言学，网络科学，和语言建模，以开发一个统一的计算框架，研究词汇搜索和检索使用的任务，广泛用于基础科学和临床环境：流畅性任务。在这项任务中，参与者被要求在一定的时间内说出尽可能多的单词，这些单词都符合一个类别（例如动物的类型）。拟议的工作将测试中心假设，即记忆搜索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验的个体差异来展开。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，以生成一个大型的语言流畅性行为数据集，并使用基于两个基本搜索机制（最佳觅食和随机游走）的新计算方法来解释哪些单词是以什么顺序产生的。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，并解释不同个体在这些任务中表现的差异。所提出的基于网络的游戏化流畅性任务，结合理论驱动的自下而上的知识表征和记忆搜索计算模型，有可能产生前所未有的流畅性数据，揭示关于记忆搜索的新见解，并开辟新的调查路线，跨越心理学和语言学领域，从而导致更强大和统一的记忆搜索认知理论。该项目由感知、行动和认知项目以及刺激竞争研究的既定项目（EPSCoR）共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。