Tikkoun Sofrim
| Autor: | Daniel Stoekl Ben Ezra, Vered Raziel-Kretzmer, Alan J. Wecker, Lily Signoret, Dror Elovits, Uri Schor, Moshe Lavee, Tsvi Kuflik, Avigail Ohali |
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| Rok vydání: | 2019 |
| Předmět: |
Computer science
business.industry 05 social sciences 020207 software engineering 02 engineering and technology Crowdsourcing Personalization Application lifecycle management World Wide Web Transcription (linguistics) 0202 electrical engineering electronic engineering information engineering Web application 0501 psychology and cognitive sciences business System structure 050107 human factors |
| Zdroj: | UMAP (Adjunct Publication) |
| DOI: | 10.1145/3314183.3324972 |
| Popis: | This paper briefly describes aspects of the Tikkoun Sofrim crowdsourcing webApp. Tikkoun Sofrim is a webApp which allows users to correct automatic transcriptions (AT) done by an AI Neural network engine. We look at the background of the crowdsourcing phenomenon in the use of automatic transcription of digital humanities documents. System structure is briefly described. We then examine personalization and adaption aspects at different stages of the user/application lifecycle Finally, we briefly list future challenges. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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