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Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.

Transcription platform Transkribus

Municipality of Amsterdam

This algorithm has low impact. Making historical handwritten documents searchable by words.

Last change on 9th of December 2024, at 14:25 (CET) | Publication Standard 1.0
Publication category
Other algorithms
Impact assessment
Field not filled in.
Status
In use

General information

Theme

Culture and Recreation

Begin date

Field not filled in.

Contact information

algoritmen@amsterdam.nl

Responsible use

Goal and impact

Making historical handwritten documents digitally accessible and searchable for researchers and other interested parties. No impact.

Considerations

Making historical research easier. This will allow more people to access historical source material.

Human intervention

The AI models were trained within the Transkribus tool by City Archive staff. The computer-read texts (HTR) were not subsequently corrected by humans, so there may be errors in the characters read

Risk management

The risks are low. The City Archives does not process non-public documents with HTR. Transkribus originated from an EU Horizon 2020 programme a then developed into a European cooperative with a large number of international heritage institutions as members. All data and metadata are hosted on European servers and are GDPR and AVG compliant.

Operations

Data

Transcriptions and Ground Truth
The dataset contains machine-read transcriptions and Ground Truth (training material) of historical manuscripts from the notarial archives, the Public Works archive and the public section of the Civil Registry. New scans with HTR are added periodically. The training material consists of tens of thousands of transcriptions made by volunteers and staff of the Stadsarchief Amsterdam.

Technical design

Using machine learning and Handwritten Text Recognition (HTR) techniques, AI models are trained to recognise manuscripts. Both of 17th-century and more modern manuscripts.

Architecture of the model
The HTR was implemented with several specific and generic AI models within Transkribus, using convolutional neural networks and transformer neural networks.

External provider

Transkribus

Link to code base

https://transkribus.eu/r/amsterdam-city-archives

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