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by avyeed_desa
1397 days ago
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I like Transkribus a lot and it is extremely helpful to get quick transcriptions, especially when the models are trained well. It will never get to 100%, but manual intervention is always needed. And Transkribus is a really, realls well-thought out piece of software, even though its heavy dependencies on Java make it slow, especially on 50+ page documents. However, i never liked their move from a research project to a commercial model. Their signup has plenty of credits for an individual who just wants to edit their family documents, but i still think it should be a bit more lenient for personal use. Thankfully there is eScriptorium. Even if it is still in early development it is a more user-friendly alternative to Transkribus.
https://gitlab.com/scripta/escriptorium |
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1. Indeed, a publicly funded European research project turned commercial software (closed source?) that expects institutions to pay for annual fees. Hmm. I understand OSS still needs constributors and has ongoing maintenance costs, but couldn’t there be a more efficient way? It had a very German academic feel to me (nofi, and indeed it’s an endeavor started at 4 German universities.)
2. The blogpost almost reads like a nineties description of the value of IT. (Fun read and perspective though! This is the positivist approach to history that underpins many interpretive histories of the future. Great and underestimated work.) The whole point of computer and user augmenting each other continuously somewhat falls short with the author saying how impressive, but fallible students and computers are. Along the lines of “okay, the output is x 1000 and of pretty good quality, but it’s not professional academic quality”. When I think of chess, or poker: computers have given people /new ways of studying/ even before applying. I think that point is still missed here. The software should point out mistakes by the students in training, while it learns by the additional input. That is the virtuous cycle of continuous improvement.
And 3. Things like the scientific R and Python ecosystems, or like Stan have shown me the power of creating open source tools for other use. Like Andrew Gelman, who has remarked multiple times that he never could have expected the use cases Stan has now. (There are Bayesian sport scientist now..!) Teach people and give them tools, but don’t dictate the entire workflow. Please let outsiders have a chance of swapping models, doing proof of concepts etc.