Work

Automatic Compositor Attribution in the First Folio of Shakespeare

Year: 2017

Type: conference-paper

Abstract: Compositor attribution, the clustering of pages in a historical printed document by the individual who set the type, is a bibliographic task that relies on analysis of orthographic variation and inspection of visual details of the printed page.In this paper, we introduce a novel unsupervised model that jointly describes the textual and visual features needed to distinguish compositors.Applied to images of Shakespeare's First Folio, our model predicts attributions that agree with the manual judgements of bibliographers with an accuracy of 87%, even on text that is the output of OCR.

Source: Proceedings of the conference - Association for Computational Linguistics. Meeting

DOI: 10.18653/v1/p17-2065

Authors: Maria Ryskina, Hannah Alpert-Abrams, Dan Garrette, Taylor Berg-Kirkpatrick

Institutions: Carnegie Mellon University, The University of Texas at Austin, Google (United States)

Language: English

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: National Science Foundation

Award: RI: Small: Collaborative Research: Unsupervised Transcription of Early Modern Documents