Oral History and technology

In Munich, from 19 to 21 September 2018, a group of speech technologists, social scientists, linguists, computer scientists, oral historians and information scientists convened to explore the integration of digital tools in the workflow of scholars who work with interviews

Cross Disciplinary Overtures with Interview Data: Integrating Digital Practices and Tools in the Scholarly Workflow

There is much talk about the need for multidisciplinary approaches to research and the opportunities that have been created by digital technologies. A good example of this is the CLARIN Portal, that promotes and supports such research by offering a large suite of tools for working with textual and audio-visual data. Yet scholars who work with interview material are largely unaware of this resource and are still predominantly oriented towards familiar traditional research methods. To reach out to these scholars and assess the potential for integration of these new technologies a multidisciplinary international community of experts set out to test CLARIN-type approaches and tools on different scholars by eliciting and documenting their feedback. This was done through a series of workshops held from 2016 to 2019, and funded by CLARIN and affiliated EU funding. This paper presents the goals, the tools that were tested and the evaluation of how they were experienced. It concludes by setting out envisioned pathways for a better use of the CLARIN family of approaches and tools in the area of qualitative and oral history data analysi

Speech, Voice, Text, and Meaning A Multidisciplinary Approach to Interview Data through the use of digital tools

Interview data is multimodal data: it consists of speech sound, facial expression and gestures, captured in a particular situation, and containing textual information and emotion. This workshop shows how a multidisciplinary approach may exploit the full potential of interview data. The workshop first gives a systematic overview of the research fields working with interview data. It then presents the speech technology currently available to support transcribing and annotating interview data, such as automatic speech recognition, speaker diarization, and emotion detection. Finally, scholars who work with interview data and tools may present their work and discover how to make use of existing technology