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Integrating Corpus-Linguistic and Conversation-Analytic Transcription in XML: The Case of Backchannels and Overlap in Storytelling Interaction

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Abstract

This paper sketches out and illustrates the research opportunities that come with the recent addition to BNCweb of very large numbers of audio files for the spoken component in the BNC. It aims to demonstrate that the availability of the audio files enables researchers not only to correct the orthographic transcripts, but also to re-transcribe the conversations using conversation-analytic transcription. It also shows that the CA transcripts can be integrated into the BNC’s XML annotation network and illustrates how XML query tools such as XPath and XQuery can be used to efficiently exploit the XML network. The main thrust of the paper is to argue that the integration of corpus-linguistic and conversation-analytic transcription in XML can make major contributions both to CL and CA. CL research into conversation can for the first time be performed on the basis of transcription that is “detailed enough to facilitate the analyst’s quest to discover and describe orderly practices of social action in interaction” (Hepburn and Bolden, in: Sidnell, Stivers (eds) The handbook of conversation analysis, Wiley Malden, 2013: 58) while CA research can gain a large-scale quantitative basis to substantiate claims about the generalizability of observed regularities and patterns in talk-in-interaction. To illustrate the benefits of doing research on re-transcriptions of the BNC’s audio files, a case study is presented on backchannels occurring in overlap in storytelling interaction. The case study reveals, inter alia, that backchannels produced by story recipients simultaneously with parts of the storyteller’s ongoing turn tend to increase in frequency as the storytelling reaches its climax. Backchannel overlap is thus in synchrony with story organization. This finding adds weight to Goodwin’s observation that recipients attend to the task “not simply of listening to the events being recounted but rather of distinguishing different subcomponents of the talk in terms of the alternative possibilities for action they invoke” (Goodwin, in: Atkinson, Heritage (eds) Structures of social action: studies in conversation analysis, Cambridge University Press, Cambridge, 1984: 243). The case study also presents exploratory evidence to suggest that, arguably due to the extended length of storytelling turns (Ochs and Capps in Living narrative, Harvard University Press, Cambridge, 2001), the proportion of overlap in running speech may be considerably lower in storytelling than in general conversation and telephone conversation.

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Notes

  1. The C-ORAL-ROM project started a tradition continued by Brazilian Portuguese, C-ORAL-BRASIL; Japanese, C-ORAL-JAPAN; and Chinese C-ORAL-CHINA.

  2. In Levinson and Torreira (2015) the percentage of 5% refers to overlap in turns including all silent parts, i.e., inter- and intra-speaker pauses; when silent parts are excluded, the percentage is 3.8%. This proportion is clearly closer to the 3.2% obtained from the model. However, the model’s most critical coefficient, the slope, is calculated on the basis of turn lengths including silent parts. So the percentage of 3.2% is best juxtaposed to the percentage of 5%.

  3. The proportion of 8% is not stated explicitly but can be read off the cumulative distribution (summation) of response times shorter than 0 ms (overlaps) on the right hand scale (scale b) of Fig. 5 on page 289 of Norwine & Murphy’s study; I’m indebted to Mattias Heldner (personal email communication) for this pointer.

  4. Another contributing factor to greater turn length in storytelling is the significantly greater number of storyteller pauses within storytelling turns (cf. Rühlemann 2013).

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  1. University of Marburg, Marburg, Germany

    Christoph Rühlemann

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Appendix

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Table 3 XTranscript tagging scheme
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Rühlemann, C. Integrating Corpus-Linguistic and Conversation-Analytic Transcription in XML: The Case of Backchannels and Overlap in Storytelling Interaction. Corpus Pragmatics 1, 201–232 (2017). https://doi.org/10.1007/s41701-017-0018-7

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