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  • Online learning environments, such as Massive Open Online Courses (MOOCs), often rely on videos as a major component to convey knowledge. However, these videos exclude potential participants who do not understand the lecturer’s language, regardless of whether that is due to language unfamiliarity or aural handicaps. Subtitles and/or interactive transcripts solve this issue, ease navigation based on the content, and enable indexing and retrieval by search engines. Although there are several automated speech-to-text converters and translation tools, their quality varies and the process of integrating them can be quite tedious. Thus, in practice, many videos on MOOC platforms only receive subtitles after the course is already finished (if at all) due to a lack of resources. This work describes an approach to tackle this issue by providing a dedicated tool, which is closing this gap between MOOC platforms and transcription and translation tools and offering a simple workflow that can easily be handled by users with a less technicalOnline learning environments, such as Massive Open Online Courses (MOOCs), often rely on videos as a major component to convey knowledge. However, these videos exclude potential participants who do not understand the lecturer’s language, regardless of whether that is due to language unfamiliarity or aural handicaps. Subtitles and/or interactive transcripts solve this issue, ease navigation based on the content, and enable indexing and retrieval by search engines. Although there are several automated speech-to-text converters and translation tools, their quality varies and the process of integrating them can be quite tedious. Thus, in practice, many videos on MOOC platforms only receive subtitles after the course is already finished (if at all) due to a lack of resources. This work describes an approach to tackle this issue by providing a dedicated tool, which is closing this gap between MOOC platforms and transcription and translation tools and offering a simple workflow that can easily be handled by users with a less technical background. The proposed method is designed and evaluated by qualitative interviews with three major MOOC providers.show moreshow less

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Metadaten
Author details:Joseph Bethge, Sebastian SerthORCiD, Thomas StaubitzORCiDGND, Tobias Wuttke, Oliver Nordemann, Partha-Pratim Das, Christoph MeinelORCiDGND
URN:urn:nbn:de:kobv:517-opus4-516943
DOI:https://doi.org/10.25932/publishup-51694
Title of parent work (English):EMOOCs 2021
Subtitle (English):A Pipeline for Automated Transcription and Translation of Videos
Publisher:Universitätsverlag Potsdam
Place of publishing:Potsdam
Publication type:Article
Language:English
Date of first publication:2021/06/30
Publication year:2021
Publishing institution:Universität Potsdam
Publishing institution:Universitätsverlag Potsdam
Release date:2021/09/20
Volume:2021
Number of pages:16
First page:79
Last Page:94
RVK - Regensburg classification:ST 670
Organizational units:Digital Engineering Fakultät / Hasso-Plattner-Institut für Digital Engineering GmbH
DDC classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Peer review:Referiert
Publishing method:Universitätsverlag Potsdam
Open Access / Gold Open-Access
Collection(s):Universität Potsdam / Sammelwerke (nicht fortlaufend) / EMOOCs 2021 / Beiträge
License (German):License LogoCC-BY - Namensnennung 4.0 International
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