You can find the newest version of the CASE transcription conventions here:
Please use the following citation:
The taxonomy used for the transcription of laughter in CASE merely describes the laughter form, but leaves the analysis of its function to the researcher’s interpretation (Brunner, Diemer & Schmidt 2017).
The following laughter sounds are differentiated in CASE:
Please use the following citation:
A taxonomy of non-verbal elements
The CASE annotation scheme tries to refrain, as far as possible, from interpreting during annotation in order to make the transcripts as objective as possible, leaving it to the researchers to draw their own conclusions. The video component of CASE can be used to supplement the transcript for a more exhaustive multimodal interpretation, for example in the context of qualitative analysis.
At this point, there is no separate layer for non-verbal elements (NVEs), such as gestures, in CASE, but selected instances of non-verbal behaviour are included as part of the basic CASE transcription layer (using curly brackets, e.g. {shrugs}). Our use of the term NVE in the following includes gestures, as well as other elements that may occur, such as salient facial movements and expressions, gaze, physical stance shifts, background, or third-party interaction.
Through a data-driven approach, we have classified the salient non-verbal elements transcribed in CASE and developed the taxonomy of NVEs which is available here.
Please use the following citation:
We are extremely grateful to our project partners at Birmingham City University's Research and Development Unit for English Studies, who are developing software to support the analysis of the transcribed spoken data. Their CASE XML Conversion tool converts the project's default mark-up to a bespoke XML schema, encapsulating all of the original information in a machine readable form. This XML version of the transcripts will enable additional levels of computational analysis. You can learn more about their project here.
The software used to convert the data into XML format was developed by Matt Gee and incorporated into the XTranscript tool.
Gee, M. (2018). XTranscript [Computer program]. Available at: http://rdues.bcu.ac.uk/cgi-bin/xtranscript/convert.cgi.
The CASE annotation scheme tries to refrain, as far as possible, from interpreting during annotation in order to make the transcripts as objective as possible, leaving it to the researchers to draw their own conclusions. The video component of CASE can be used to supplement the transcript for a more exhaustive multimodal interpretation, for example in the context of qualitative analysis.
At this point, there is no separate layer for non-verbal elements (NVEs), such as gestures, in CASE, but selected instances of non-verbal behaviour are included as part of the basic CASE transcription layer (using curly brackets, e.g. {shrugs}). Our use of the term NVE in the following includes gestures, as well as other elements that may occur, such as salient facial movements and expressions, gaze, physical stance shifts, background, or third-party interaction.
Through a data-driven approach, we have classified the salient non-verbal elements transcribed in CASE and developed the taxonomy of NVEs which is available here.
Please use the following citation:
CASE Taxonomy of non-verbal elements. (May 2017). Birkenfeld: Trier University of Applied Sciences. [http://umwelt-campus.de/case-conventions]
The taxonomy used for the transcription of laughter in CASE merely describes the laughter form, but leaves the analysis of its function to the researcher’s interpretation (Brunner, Diemer & Schmidt 2017).
The following laughter sounds are differentiated in CASE:
Please use the following citation:
CASE laughter transcription. (May 2017). Birkenfeld: Trier University of Applied Sciences. [ http://umwelt-campus.de/case-conventions]
We are extremely grateful to our project partners at Birmingham City University's Research and Development Unit for English Studies, who are developing software to support the analysis of the transcribed spoken data. Their CASE XML Conversion tool converts the project's default mark-up to a bespoke XML schema, encapsulating all of the original information in a machine readable form. This XML version of the transcripts will enable additional levels of computational analysis. You can learn more about their project here.
The software used to convert the data into XML format was developed by Matt Gee and incorporated into the XTranscript tool.
Gee, M. (2018). XTranscript [Computer program]. Available at: http://rdues.bcu.ac.uk/cgi-bin/xtranscript/convert.cgi.
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