arXiv cs.CL· Tamas Kovacs, Daniel Luger·· 13 小时前AI 评分18
利用十九世纪学术遗产为十三世纪教皇登记册构建 HTR：Regesta 与古籍版本驱动的强制对齐与自举
Mining the Nineteenth Century for the Thirteenth: Register-Scale Forced Alignment and HTR Bootstrapping via Legacy Regesta and Antiquarian Editions
AI 导读
研究测量了 Pressutti 的 regesta 与十九世纪部分版本对教皇 Honorius III 登记册手写文本识别（HTR）的贡献，在 fol. 1-203 上呈现三层分工。
正文 · 原文
Abstract:Handwritten text recognition (HTR) for the registers of Pope Honorius III depends on modern expert transcriptions, which exist only for regnal years 1-2 of Reg. Vat. 9. For the remaining registers, nineteenth-century scholarship offers Pressutti's regesta and partial editions. On fol. 1-203, where both layers exist, we measure what this legacy layer can contribute, on transcriptions that we first audit against it, and find a division of labor across three tiers. At the orthographic tier, raw editions are at best neutral for adapting a recognizer to the second regnal year and harmful without replay, whereas projection onto curial spelling with replay of modern source lines turns them into zero-label adaptation targets: pooled over all 134 year-2 sides, the WER falls by 1.50 points (95% CI -1.84 to -1.15), closing 33% of the gap to an oracle; the spelling changes at the year split, through the scribe or the transcriber, whereas the hand changes visibly only at fol. 191r. At the lexical tier, the corpus-wide legacy lexicon contains 82.2% of the out-of-vocabulary words of unedited entries and flags recognition errors with 66.7% precision, and labels from pre-trained medieval NER models, distilled into the recognizer's NER head, reach F1 82.1% on an expert validated benchmark, level with the best tagger applied after recognition. At the topological tier, Pressutti's regests, the closing datum clauses, and the regests' dates converted to the chancery's Roman form find 73.9% of entry starts in the recognized line stream, and edition agreement estimates a CER of 7.80% beyond fol. 203. Antiquarian scholarship thus cannot replace modern transcription, but it can steer, check, and segment HTR across the untranscribed registers.
| Comments: | 10 pages |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Computation and Language (cs.CL) |
| Cite as: | arXiv:2610.36956 [cs.CV] |
| (or arXiv:2610.36956v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2610.36956 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Tamás Kovács [view email]
[v1]
Tue, 27 Oct 2026 10:15:08 UTC (38 KB)
来源：arXiv cs.CL · arxiv.org