Nick Hodder, Director of Digital Engagement and Transformation,
IWM
‘ double-oos’,” Nick says.“ That’ s what digital transcription normally would provide. But the AI transcription understands: this is a sailor, he’ s on a ship, when he’ s talking about‘ ooks’, he’ s hanging things up, this must be‘ hooks’. So it understands context in a way that previous transcriptions didn’ t.”
The accuracy improvements were dramatic.“ We found with our spot checking we’ re reaching an accuracy of 99 %, which is a much lower error rate than not just digital transcription, but humans as well,” Nick reports. The efficiency gains were equally significant: the project saved“ over 20 years of manual transcription time in a matter of weeks.”
Research revolution The most significant change may be in how people investigate history.“ When you search something in the past, you might say,‘ Does this person mention this date or this place?’” Nick explains.“ But through the LLM, you could say,‘ How did they feel? Were they scared? Did they have any funny stories?’ So you’ re now introducing sentiment into research, which is really important, because when you are researching something where you want to tell someone’ s story, it’ s really important to understand how they felt.”
The implications extend beyond museums.“ As we move towards the present era, away from the Second World War, we’ ll find ourselves left with very few people alive with that direct experience of that war,” Nick observes.“ Capturing those oral histories is vitally important and enabling discovery of those stories is, I think, pivotal: not just for us as a museum, but I think for other museums and other archives capturing this history and making it discoverable.”
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