Presentation of LectAuRep (Notary Registers Automated Reading) project. HTR applied to the French National Archives Notary Registers. IA4LAM community call, September 21st 2021 (+ link to recording in downloaded pdf).

1. LectAuRep
(Notary Registers Automated Reading)
HTR applied to the French National Archives Notary Registers
Aurélia Rostaing
aurelia.rostaing@culture.gouv.fr
IA4LAM
September 21st 2021

2. - Several image
qualities
- 1000s
handwritings
(1803-1940s)
- +600,000 pages
Corpora with visually structured information

3. Serve end-users
> Turn massively digitized archives into data
through AI (recurrent neural networks - LSTM)
in order to read, search, mine text
Serve LAM communities
>Mutualize & document data, models and methods
(joint estate regime)

4. http://kraken.re/ https://gitlab.com/scripta/escriptorium
Scripta-PSL project OS softwares

5. We need to
segment,
transcribe,
correct,
annotate (NER),
in order to
modelise,
automate,
optimise,
share.

6. Transforming digital images into data

7. Ongoing results

8. Still to be worked out
Sort out a DMP & manage workflows
Crowdsource raw HTR data editing
Feed the data to our VRR & customers via a TEI pipeline
Ongoing transcriptions/ground truth/raw HTR data
Anonymous full-text search (flat data)
Fuzzy + NER-based search (TEI)
Ground truth (EAD - RiC)

9. Feeding this data to
our VRR & customers
Raw ground truth
Partly edited ground truth

10. Editing text & structure for reading and research
https://github.com/HugoSchtr
https://gitlab.inria.fr/almanach/lectaurep/lepidemo

11. Further Reading on LectAuRep, eScripta & HTR
https://lectaurep.hypotheses.org
https://gitlab.inria.fr/almanach/lectaurep
https://escripta.hypotheses.org/
https://gitlab.com/scripta/escriptorium
https://gitlab.inria.fr/almanach/lectaurep/lepidemo
http://kraken.re/
https://readcoop.eu/transkribus
https://teklia.com/