<i>Li Seint Confessor </i>de Wauchier de Denain, une œuvre sérielle et son contexte manuscrit

Pinche, Ariane

doi:10.1484/m.hag-eb.5.126288

Cited by 2 publications

(2 citation statements)

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“…As the dataset is made from pre-existing transcriptions, the sample size is very different from one source manuscript to the other. The basis of the dataset is composed of a graphemic transcription (see after for the transcription principles) of La Vie de saint Martin and of the Dialogues sur les vertus de saint Martin from the hagiographic collection Li Seint Confessor of Wauchier de Denain (Pinche [2021b]). It is supplemented with carefully aligned data from other projects: transcriptions 11 of Chanson d'Otinel (Camps [2017]) from the Geste project 12 , transcription of Manuscrit du Roi for the Maritem project 13 , crowdsourced transcriptions of the collaborative projects of the Standford Library: Image du Monde (BnF.…”

Section: Datasetmentioning

confidence: 99%

Artificial colorization of digitized microfilms: a preliminary study

Clérice¹,

Pinche²

2023

Journal of Data Mining &Amp; Digital Humanities

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A lot of available digitized manuscripts online are actually digitized microfilms, a technology dating back from the 1930s. With the progress of artificial colorization, we make the hypothesis that microfilms could be colored with these recent technologies, testing InstColorization. We train a model over an ad-hoc dataset of 18 788 color images that are artificially gray-scaled for this purpose. With promising results in terms of colorization but clear limitations due to the difference between artificially grayscaled images and "naturaly" greyscaled microfilms, we evaluate the impact of this artificial colorization on two downstream tasks using Kraken: layout analysis and text recognition. Unfortunately, the results show little to no improvements which limits the interest of artificial colorization on manuscripts in the computer vision domain.

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Section: Datasetmentioning

confidence: 99%

Artificial colorization of digitized microfilms: a preliminary study

Clérice¹,

Pinche²

2023

Journal of Data Mining &Amp; Digital Humanities

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“…We started with the Vie de Saint Martin de Wauchier de Denain from the manuscript BnF fr. 412 for which we had a diplomatic transcription [Pinche, 2021]. We, then, aligned transcriptions from "transcribathons" organized by Laura Morreale (Stanford Libraries projects) or from projects hosted by the Ecole nationale des chartes 12 , adapting if necessary the pre-existing transcription.…”

Section: Gathering Data and Data Qualitymentioning

confidence: 99%

Generic HTR Models for Medieval Manuscripts. The CREMMALab Project

Pinche

2023

Journal of Data Mining &Amp; Digital Humanities

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In the Humanities, the emergence of digital methods has opened up research questions to quantitative analysis. This is why HTR technology is increasingly involved in humanities research projects following precursors such as the Himanis project. However, many research teams have limited resources, either financially or in terms of their expertise in artificial intelligence. It may therefore be difficult to integrate handwritten text recognition into their project pipeline if they need to train a model or to create data from scratch. The goal here is not to explain how to build or improve a new HTR engine, nor to find a way to automatically align a preexisting corpus with an image to quickly create ground truths for training. This paper aims to help humanists easily develop an HTR model for medieval manuscripts, create and gather training data by knowing the issues underlying their choices. The objective is also to show the importance of the constitution of consistent data as a prerequisite to allow their gathering and to train efficient HTR models. We will present an overview of our work and experiment in the CREMMALab project (2021-2022), showing first how we ensure the consistency of the data and then how we have developed a generic model for medieval French manuscripts from the 13 th to the 15 th century, ready to be shared (more than 94% accuracy) and/or fine-tuned by other projects.

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Li Seint Confessor de Wauchier de Denain, une œuvre sérielle et son contexte manuscrit

Cited by 2 publications

References 0 publications

Artificial colorization of digitized microfilms: a preliminary study

Artificial colorization of digitized microfilms: a preliminary study

Generic HTR Models for Medieval Manuscripts. The CREMMALab Project

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