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Glyph norming: Human and computational measurements of shape angularity in writing systems
Alexander Porto1, Nikolai Huckle2, Alexander Basalyga2
1Department of Psychology, Duquesne University, 600 Forbes Avenue, Pittsburgh, PA, 15219, USA. portoa1@duq.edu.
Behavior Research Methods
|May 14, 2025
Summary
This study introduces a new database of 3,208 writing system glyphs, computationally analyzed for shape angularity. Human judgments highly correlate with these measures, enabling new research in cognitive psychology and linguistics.
Area of Science:
- Cognitive psychology
- Psycholinguistics
- Anthropology
- Computer Vision
Background:
- Writing systems are rich, yet underutilized, stimuli for cognitive science research.
- Glyph complexity has historically limited their use in behavioral experiments.
- Advances in computational vision enable objective shape analysis.
Purpose of the Study:
- To create an open-access database of normed writing system glyphs.
- To computationally analyze glyphs for shape angularity.
- To validate computational measures with human perception.
Main Methods:
- Developed computational analyses for shape angularity using geometric shape analysis.
- Created a database of 3,208 glyphs from diverse writing systems.
- Validated computational norms with human judgments on 400 glyphs.
- Provided methods for standardized glyph generation and automated transliteration.
Main Results:
- Established a comprehensive database of computationally normed glyphs.
- Demonstrated high correlation between computational angularity measures and human perception.
- Showcased the utility of computational shape analysis for visual stimuli.
Conclusions:
- Computational shape analysis offers a robust method for characterizing visual stimuli like glyphs.
- The developed database and methods facilitate research in cognitive science subdisciplines.
- This work promotes the use of writing systems as stimuli in behavioral and computational research.
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