Oral history – the practice of eliciting and recording people’s personal memory of lived experiences – has benefited enormously from the growth of digital technology. However, the software available is often not fully exploited by researchers in the humanities and the social sciences, and oral history data is somewhat underused by linguists. To address this state of affairs the CLARIN-PLUS project (which continues work done by its predecessor CLARIN) is hosting a two-day workshop in IT Services on Monday 18 and Tuesday 19 April.
Exploring Spoken Word Data in Oral History Archives will bring together experts in language and speech technology, archivists, and researchers from a number of disciplines working with oral history archives. The event will focus on the following questions:
- What language technologies exist and can be used to help explore and analyse collections?
- What are the barriers to uptake for these tools, and what can CLARIN do to take them away?
- How can we integrate disparate collections to make more coherent historical collections, language corpora, and virtual collections?
- Can we identify themes that could be studied from a cross-European (comparative) perspective and what could CLARIN do to support such studies?
The outcomes of the workshop will include:
- Proposals for new resource development and integration in CLARIN;
- Proposals for new future joint research projects;
- Requirements for the tools and services that could support of researchers working with oral history data, including ideas for tutorial development.
Places are still available. So, if you use oral history archive data in your research and you’re curious about language technology tools, get in touch with Martin Wynne of the Academic IT Research Support Team: email@example.com.
The workshop is organised in partnership with the Phonetics Laboratory and the e-Research Centre at the University of Oxford.
CLARIN is the Common Language Resources and Technology Infrastructure, which provides easy and sustainable access for scholars in the humanities and social sciences to digital language data, and advanced tools for working with such data.