Preliminary Programme

Wed 18 March
    08.30 - 10.30
    11.00 - 13.00
    14.00 - 16.00
    16.30 - 18.30

Thu 19 March
    08.30 - 10.30
    11.00 - 13.00
    14.00 - 16.00
    16.30 - 18.30

Fri 20 March
    08.30 - 10.30
    11.00 - 13.00
    14.00 - 16.00
    16.30 - 18.30

Sat 21 March
    08.30 - 10.30
    11.00 - 13.00
    14.00 - 16.00
    16.00 - 17.00

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Wednesday 18 March 2020 14.00 - 16.00
R-3 ORA14 Transcribing Oral History Interviews (Semi-)automatically. Technological Promises in Practical Testing
Lipsius, 307
Network: Oral History Chairs: -
Organizers: Almut Leh, Cord Pagenstecher Discussants: -
Christoph Draxler : Web-based Tools for Transcribing and Segmenting Speech
The Bavarian Archive for Speech Signals (BAS) provides a number of web-based speech processing services such as online editors, multilingual automatic seg-mentation, anonymisation and subtitling. In my current research, I am looking at the potential benefits of ASR for transcription, and on determining on how to pre-dict ASR quality automatically.

Peter Kompiel : Testing (Semi-)automatic Transcription Tools
For the creation of new interview collections at Freie Universität Berlin, the pro-cess of time-coded transcription should be as efficient and streamlined as possi-ble. Therefore, various (semi)automatic transcription tools have been tested, tak-ing recognition quality, usability and the support of established workflows as criteria.

Almut Leh : Audiomining – Advanced Speech Technologies for Transcribing, Indexing and Analysing Oral History Interviews
Audiomining is a tool for analysing spoken speech with direct access to the audio signal. In addition to the conversion into text, timecodes are set with word accu-racy. This allowed the synchronous representation of audio/video and transcript in the form of subtitles. In the interpretation of oral history interviews, this ... (Show more)
Audiomining is a tool for analysing spoken speech with direct access to the audio signal. In addition to the conversion into text, timecodes are set with word accu-racy. This allowed the synchronous representation of audio/video and transcript in the form of subtitles. In the interpretation of oral history interviews, this can direct the focus from the text to the original source, the spoken word. (Show less)

Cord Pagenstecher : Creating Transcripts for Large Interview Collections
The manual creation of large numbers of transcripts have been a core element of the curation and archiving of the digital interview collections available at Freie Universität Berlin. While different approaches have been used in the individual, manifold and multilingual collections, the need for sustainability and interoperabil-ity raises new requirements ... (Show more)
The manual creation of large numbers of transcripts have been a core element of the curation and archiving of the digital interview collections available at Freie Universität Berlin. While different approaches have been used in the individual, manifold and multilingual collections, the need for sustainability and interoperabil-ity raises new requirements and challenges. (Show less)

Thorsten Pehl : Establishing a Workflow for the Use of Speech Recognition
The productive use of speech recognition requires not only precise algorithms, but also concepts for data protection and rapid correction of transcripts. For this purpose, the results of the research on the relationship between error rate and correction duration as well as a procedural concept for the implementation of data ... (Show more)
The productive use of speech recognition requires not only precise algorithms, but also concepts for data protection and rapid correction of transcripts. For this purpose, the results of the research on the relationship between error rate and correction duration as well as a procedural concept for the implementation of data transfer under data protection law are presented. (Show less)



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