Indexing oral histories digitally at the timecode level is a practice increasingly adopted for collections, often with the goal of creating online access to recordings. A particular attraction to using an index is that it can be generated in less time than a transcript, especially when both must be done manually. Indexing provides convenient access to original recordings and can be a platform for decision-making about a collection over time, for researchers or collection stewards. In my current work in digital oral history at the University of Luxembourg’s Centre for Contemporary and Digital History (C2DH), indexing is being embraced for these strategic and practical benefits. However, indexing approaches I promoted previously in the US will need to be re-envisioned, retooled, and otherwise adapted for new and different cultural and technological contexts.
In Europe, many oral history projects tend to be focused on journalistic-style research, so the goal of recording and indexing is different; curating, archiving, and publishing recordings is not necessarily expected or assumed. In Luxembourg and elsewhere in Europe, there is great interest in applying technology-centered analyses to oral history corpora (e.g., topic modeling, sentiment analysis, corpus linguistics, etc.), work predicated on high-quality transcripts rather than indexing. At the same time, improvements have been made in other technology/transcript-centered methods of analysis, such as keyword extraction, named entity recognition, and automated indexing—all of which could advance and improve oral history indexing and analysis practice. These new approaches will be more viable as speech recognition technology continues to improve, making transcripts easier and cheaper to create. As these factors converge, a new balance between transcription, indexing, and human interpretation will develop that supports both conventional oral history uses as well as secondary collection research activities.
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