搜索器:一个Python包和用于模拟心理搜索的Web界面
Abhilasha A Kumar1, Molly Apsel2, Larry Zhang2
1Bowdoin College, Brunswick, ME, USA. a.kumar@bowdoin.edu.
Behavior research methods
|December 12, 2023
概括
研究人员现在可以使用"forager"Python包分析内存搜索模式. 这个工具简化了记忆研究人员和临床医生的口头流利任务的计算建模.
科学领域:
- 认知心理学 认知心理学
- 计算神经科学是一种神经科学.
- 心理语言学 心理语言学
背景情况:
- 语言流利性任务对于理解记忆搜索和检索至关重要.
- 现有的计算模型为内存搜索机制提供了洞察力.
- 在应用和比较这些模型的可访问工具中存在差距.
研究的目的:
- 介绍"forager",一个开源的Python包和Web接口.
- 为分析语言流数据提供自动化方法.
- 为了方便应用和比较用于内存搜索的计算模型.
主要方法:
- 开发了"forager"Python包和Web界面的开发.
- 实现自动集群和切换检测算法的实现.
- 整合使用语义嵌入的新型计算模型来分析对记忆搜索的词汇影响 (语义,语音,频率).
主要成果:
- "Forager"提供口语流度列表的自动分析,识别集群和开关.
- 该软件包可以在个人和团体层面评估计算模型.
- 与现有的行为和临床语义流性数据集的证明实用性.
结论:
- "Forager"消除了在流利性任务中研究内存搜索的编程障碍.
- 该工具支持具有不同编程专业知识的研究人员和临床医生.
- 为内存搜索的计算建模提供了一个统一的平台.
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