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  pretty_name: CATMuS Medieval
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  size_categories:
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  - 100K<n<1M
 
 
 
 
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  ---
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- # Dataset Card for Dataset Name
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- <!-- Provide a quick summary of the dataset. -->
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- This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
 
 
 
 
 
 
 
 
 
 
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- ## Dataset Details
 
 
 
 
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  ### Dataset Description
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  <!-- Provide a longer summary of what this dataset is. -->
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-
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- - **Curated by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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-
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  ### Dataset Sources [optional]
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- <!-- Provide the basic links for the dataset. -->
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  - **Repository:** [More Information Needed]
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  - **Paper [optional]:** [More Information Needed]
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  - **Demo [optional]:** [More Information Needed]
 
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  ## Uses
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- <!-- Address questions around how the dataset is intended to be used. -->
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-
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  ### Direct Use
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- <!-- This section describes suitable use cases for the dataset. -->
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-
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- [More Information Needed]
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  ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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-
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- [More Information Needed]
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  ## Dataset Structure
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- <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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-
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- [More Information Needed]
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  ## Dataset Creation
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  ### Curation Rationale
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- <!-- Motivation for the creation of this dataset. -->
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  [More Information Needed]
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  ### Source Data
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- <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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  #### Data Collection and Processing
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- <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
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  [More Information Needed]
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  #### Who are the source data producers?
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- <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
 
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  [More Information Needed]
 
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  ### Annotations [optional]
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- <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
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-
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  #### Annotation process
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- <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
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- [More Information Needed]
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  #### Who are the annotators?
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- <!-- This section describes the people or systems who created the annotations. -->
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- [More Information Needed]
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-
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- #### Personal and Sensitive Information
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- <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
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- [More Information Needed]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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  ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
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  **BibTeX:**
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- [More Information Needed]
 
 
 
 
 
 
 
 
 
 
 
 
 
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  **APA:**
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- [More Information Needed]
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  ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- [More Information Needed]
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- ## Dataset Card Authors [optional]
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- [More Information Needed]
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  ## Dataset Card Contact
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- [More Information Needed]
 
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  pretty_name: CATMuS Medieval
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  size_categories:
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  - 100K<n<1M
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+ tags:
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+ - optical-character-recognition
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+ - humanities
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+ - handwritten-text-recognition
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  ---
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+ # Dataset Card for CATMuS Medieval
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+ ## Dataset Details
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+ Handwritten Text Recognition (HTR) has emerged as a crucial tool for converting manuscripts images into machine-readable formats,
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+ enabling researchers and scholars to analyse vast collections efficiently.
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+ Despite significant technological progress, establishing consistent ground truth across projects for HTR tasks,
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+ particularly for complex and heterogeneous historical sources like medieval manuscripts in Latin scripts (8th-15th century CE), remains nonetheless challenging.
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+ We introduce the **Consistent Approaches to Transcribing Manuscripts (CATMuS)** dataset for medieval manuscripts,
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+ which offers:
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+ 1. a uniform framework for annotation practices for medieval manuscripts,
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+ 2. a benchmarking environment for evaluating automatic text recognition models across multiple dimensions thanks to rich metadata (century of production,
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+ language, genre, script, etc.),
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+ 3. a benchmarking environment for other tasks (such as script classification or dating approaches),
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+ 4. a benchmarking environment and finally for exploratory work pertaining to computer vision and digital paleography around line-based tasks, such as generative approaches.
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+ Developed through collaboration among various institutions and projects, CATMuS provides an inter-compatible dataset spanning more than 200 manuscripts and incunabula in 10
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+ different languages, comprising over 160,000 lines of text and 5 million characters spanning from the 8th century to the 16th.
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+
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+ The dataset's consistency in transcription approaches aims to mitigate challenges arising from the diversity in standards for medieval manuscript transcriptions,
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+ providing a comprehensive benchmark for evaluating HTR models on historical sources.
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  ### Dataset Description
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  <!-- Provide a longer summary of what this dataset is. -->
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+ - **Curated by:** Thibault Clérice
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+ - **Funded by:** BnF Datalab, Biblissima +, DIM PAMIR
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+ - **Language(s) (NLP):** Middle and Old French, Middle Dutch, Catalan, Spanish, Navarese, Italian, Venitian, Old English, Latin
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+ - **License:** CC-BY
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+ <!--
 
 
 
 
 
 
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  ### Dataset Sources [optional]
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+ Provide the basic links for the dataset.
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  - **Repository:** [More Information Needed]
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  - **Paper [optional]:** [More Information Needed]
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  - **Demo [optional]:** [More Information Needed]
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+ -->
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  ## Uses
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  ### Direct Use
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+ - Handwritten Text Recognition
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+ - Data classification
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+ - Script classification
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  ### Out-of-Scope Use
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+ - Text-To-Image
 
 
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  ## Dataset Structure
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+ - Data contains the main `split` that is loaded through `load_dataset("CATMuS/medieval")`
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+ - Data can be split with each manuscript inside train, val and test using the `gen_split` columns which results in a 90/5/5 split
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+ - The image is in the `im` column, and the text in the `text` column
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+ <!--
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  ## Dataset Creation
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  ### Curation Rationale
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+ Motivation for the creation of this dataset.
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  [More Information Needed]
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  ### Source Data
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+ This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...).
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  #### Data Collection and Processing
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+ <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc.
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  [More Information Needed]
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  #### Who are the source data producers?
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+ <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if
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+ this information is available.
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  [More Information Needed]
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+ -->
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  ### Annotations [optional]
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  #### Annotation process
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+ The annotation process is described in the [dataset paper](https://inria.hal.science/hal-04453952).
 
 
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  #### Who are the annotators?
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+ - Pinche, Ariane
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+ - Clérice, Thibault
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+ - Chagué, Alix
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+ - Camps, Jean-Baptiste
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+ - Vlachou-Efstathiou, Malamatenia
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+ - Gille Levenson, Matthias
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+ - Brisville-Fertin, Olivier
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+ - Boschetti, Federico
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+ - Fischer, Franz
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+ - Gervers, Michael
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+ - Boutreux, Agnès
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+ - Manton, Avery
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+ - Gabay, Simon
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+ - Bordier, Julie
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+ - Glaise, Anthony
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+ - Alba, Rachele
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+ - Rubin, Giorgia
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+ - White, Nick
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+ - Karaisl, Antonia
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+ - Leroy, Noé
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+ - Maulu, Marco
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+ - Biay, Sébastien
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+ - Cappe, Zoé
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+ - Konstantinova, Kristina
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+ - Boby, Victor
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+ - Christensen, Kelly
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+ - Pierreville, Corinne
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+ - Aruta, Davide
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+ - Lenzi, Martina
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+ - Le Huëron, Armelle
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+ - Possamaï, Marylène
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+ - Duval, Frédéric
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+ - Mariotti, Violetta
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+ - Morreale, Laura
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+ - Nolibois, Alice
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+ - Foehr-Janssens, Yasmina
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+ - Deleville, Prunelle
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+ - Carnaille, Camille
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+ - Lecomte, Sophie
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+ - Meylan, Aminoel
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+ - Ventura, Simone
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+ - Dugaz, Lucien
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  ## Bias, Risks, and Limitations
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+ The data are skewed toward Old French, Middle Dutch and Spanish, specifically from the 14th century.
 
 
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+ The only language that is represented over all centuries is Latin, and in each scripts. The other language with a coverage close to Latin is Old French.
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+ Only one document is available in Old English.
 
 
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  ## Citation [optional]
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  **BibTeX:**
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+ ```tex
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+ @unpublished{clerice:hal-04453952,
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+ TITLE = {{CATMuS Medieval: A multilingual large-scale cross-century dataset in Latin script for handwritten text recognition and beyond}},
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+ AUTHOR = {Cl{\'e}rice, Thibault and Ariane, Pinche and Malamatenia, Vlachou-Efstathiou and Alix, Chagu{\'e} and Jean-Baptiste, Camps and Matthias, Gille-Levenson and Olivier, Brisville-Fertin and Franz, Fischer and Michaels, Gervers and Agn{\`e}s, Boutreux and Avery, Manton and Simon, Gabay and Patricia, O'Connor and Wouter, Haverals and Mike, Kestemont and Caroline, Vandyck and Benjamin, Kiessling},
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+ URL = {https://inria.hal.science/hal-04453952},
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+ NOTE = {working paper or preprint},
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+ YEAR = {2024},
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+ MONTH = Feb,
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+ KEYWORDS = {Historical sources ; medieval manuscripts ; Latin scripts ; benchmarking dataset ; multilingual ; handwritten text recognition},
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+ PDF = {https://inria.hal.science/hal-04453952/file/ICDAR24___CATMUS_Medieval-1.pdf},
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+ HAL_ID = {hal-04453952},
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+ HAL_VERSION = {v1},
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+ }
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+ ```
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  **APA:**
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+ > Thibault Clérice, Pinche Ariane, Vlachou-Efstathiou Malamatenia, Chagué Alix, Camps Jean-Baptiste, et al.. CATMuS Medieval: A multilingual large-scale cross-century dataset in Latin script for handwritten text recognition and beyond. 2024. ⟨hal-04453952⟩
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  ## Glossary [optional]
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+ - Scripts: In the middle ages, the writing style changed over time, specifically in "litterary" manuscripts, for which we call the general scripts "Bookscripts". This is what CATMuS Medieval covers at the time
 
 
 
 
 
 
 
 
 
 
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  ## Dataset Card Contact
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+ Thibault Clérice ([email protected])