一个计算框架来研究视觉叙事中的等级处理
Aditya Upadhyayula1, Neil Cohn2
1Department of Psychological & Brain Sciences, Washington University in St. Louis.
Cognitive science
|May 3, 2025
概括
本研究介绍了一个计算框架,用于探索视觉叙事理解中的等级结构. 研究结果表明,人类处理与等级语法保持一致,与平面化模型不同.
科学领域:
- 认知科学 认知科学
- 计算语言学 计算语言学
- 心理语言学 心理语言学
背景情况:
- 视觉叙事理解理论经常提出基于语法的等级机制.
- 对视觉叙事的等级性质的实证研究仍然有限.
研究的目的:
- 开发和测试用于分析视觉叙事中的层次结构的计算框架.
- 将计算模型与行为数据进行比较,以推断认知处理机制.
主要方法:
- 由心理语言学启发的计算框架被开发出来.
- 一个细分任务被用来收集在视觉叙事边界上的行为数据.
- 为了预测细分偏好,使用了三个模型 (Earley解析器,隐藏的马尔科夫模型,n-gram).
主要成果:
- 视觉叙事语法显著预测了参与者细分偏好.
- 厄利的解析器,利用层次语法与递归,比平面语法模型 (HMM,n-gram) 更好地匹配行为数据.
结论:
- 人类视觉叙事理解似乎涉及层次处理,与语法结构一致.
- 这项研究为了解超越语言系统的心理表征的认知架构开辟了新的途径.
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