# Theatre Chapbooks At Scale: A Statistical Comparative Analysis of Typography

arXiv: https://arxiv.org/abs/2607.27266 · HTML: https://mlsanity.com/paper/2607.27266/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 32 references that are in the map.
- First posted on arXiv 29 Jul 2026.

## Builds on (most cited first, 7 of 7)

- [UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction](https://mlsanity.com/paper/1802.03426/) (2018)
- [Convolutional Character Networks](https://mlsanity.com/paper/1910.07954/) (2019)
- [An Interpretable Deep Learning Approach for Morphological Script Type Analysis](https://mlsanity.com/paper/2408.11150/) (2024)
- [Improving OCR using internal document redundancy](https://mlsanity.com/paper/2508.14557/) (2025)
- [Automatic Compositor Attribution in the First Folio of Shakespeare](https://mlsanity.com/paper/1704.07875/) (2017)
- [Contrastive Attention Networks for Attribution of Early Modern Print](https://mlsanity.com/paper/2306.07998/) (2023)
- [Clustering Running Titles to Understand the Printing of Early Modern Books](https://mlsanity.com/paper/2405.00752/) (2024)

## Abstract (arXiv)

We propose a statistical methodology that quantifies the similarity of typefaces between printed historical books. This provides a tool that accelerates philological analysis. Using character prototypes derived from clustering and aligning automatically extracted character images, the method defines a typeface distance between any two books. To produce actionable outputs, we develop an a contrario statistical framework to interpret the significance of the computed typeface distances. We apply the method to the philological study of 17 th -century Spanish printed theatre chapbooks in a quantity that exceeds the capabilities of systematic visual inspection by human experts. Our method enables the automatic comparison of Roman and Italic types extracted from different books. After validation by human experts, our method has led to new printer attributions being discovered, and former printer attributions being revised. This success strongly suggests that our method has the potential to enable digital bibliography on a larger scale than was previously possible.