Transcribing historical handwritten documents is a difficult task. One facet is that it is a very tedious task normally performed by experts. Some newer techniques rely on crowdsourcing of manual transcription. Crowdsourcing helps speeding up the transcription process, but it is still limited and brings with it new challenges. Though crowdsourcing transcriptions can imply a repetitive task done by a large group of users, there is in fact room for personalization. This paper reports on insights gathered for future personalizations from the "Tikkoun Sofrim" project, that implements a framework for combining automatic handwritten text recognition with crowdsourcing for transcription of complete handwritten manuscripts. As a case study, the Hebrew "Midrash Tanhuma" manuscripts were selected.
|Title of host publication||UMAP 2020 Adjunct - Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||3|
|State||Published - 14 Jul 2020|
|Event||28th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2020 - Genoa, Italy|
Duration: 14 Jul 2020 → 17 Jul 2020
|Name||UMAP 2020 Adjunct - Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization|
|Conference||28th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2020|
|Period||14/07/20 → 17/07/20|
Bibliographical noteFunding Information:
The project is funded by PHC Maimonide 41146YC Thanks also to Avigail Ohali, Pawel Jablonski, Pauline Signoret and Moshe Schorr for their contributions to the project and discussions.
© 2020 ACM.
- computer assisted transcription for text images
- handwritten text recognition
ASJC Scopus subject areas