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In Codice Ratio is a research project to study tools and techniques foranalyzing the contents of historical documents conserved in the Vatican SecretArchives (VSA). In this paper, we present our efforts to develop a system tosupport the transcription of medieval manuscripts. The goal is to providepaleographers with a tool to reduce their efforts in transcribing largevolumes, as those stored in the VSA, producing good transcriptions forsignificant portions of the manuscripts. We propose an original approach basedon character segmentation. Our solution is able to deal with the dirtysegmentation that inevitably occurs in handwritten documents. We use aconvolutional neural network to recognize characters and language models tocompose word transcriptions. Our approach requires minimal training efforts,making the transcription process more scalable as the production of trainingsets requires a few pages and can be easily crowdsourced. We have conductedexperiments on manuscripts from the Vatican Registers, an unreleased corpuscontaining the correspondence of the popes. With training data produced by 120high school students, our system has been able to produce good transcriptionsthat can be used by paleographers as a solid basis to speedup the transcriptionprocess at a large scale.

Towards Knowledge Discovery from the Vatican Secret Archives. In Codice Ratio -- Episode 1: Machine Transcription of the Manuscripts