Combining Human and Machine Transcriptions on the Zooniverse Platform

Daniel Hanson, Andrea Simenstad


Abstract
Transcribing handwritten documents to create fully searchable texts is an essential part of the archival process. Traditional text recognition methods, such as optical character recognition (OCR), do not work on handwritten documents due to their frequent noisiness and OCR’s need for individually segmented letters. Crowdsourcing and improved machine models are two modern methods for transcribing handwritten documents.
Anthology ID:
W18-6129
Volume:
Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text
Month:
November
Year:
2018
Address:
Brussels, Belgium
Editors:
Wei Xu, Alan Ritter, Tim Baldwin, Afshin Rahimi
Venue:
WNUT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
215–216
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/W18-6129/
DOI:
10.18653/v1/W18-6129
Bibkey:
Cite (ACL):
Daniel Hanson and Andrea Simenstad. 2018. Combining Human and Machine Transcriptions on the Zooniverse Platform. In Proceedings of the 2018 EMNLP Workshop W-NUT: The 4th Workshop on Noisy User-generated Text, pages 215–216, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Combining Human and Machine Transcriptions on the Zooniverse Platform (Hanson & Simenstad, WNUT 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/W18-6129.pdf