Hacker News Reader

I've had a look at a few of those and I doubt you'd get 99% accuracy. A lot of the footnotes especially are very hard to decipher. They're also 50 years old, handwriting has changed over time. I'm not sure how well models are trained to read old handwriting, I know that I struggle with it.

For humans, much can be deciphered through context. That's much more complex to do with OCR.

View on HN

The National Archives in the UK has a research project to try to read > 200 year old handwriting with OCR reliably. They use various tricks like training per-century or per author models which gives a big performance improvement. They also have ways to handle symbols that no longer exist (not in unicode). Give me a shout if anyone here wants to collaborate.

I work on the visualization and publishing side of this kind of data, but I do know our HTR works even better if we combine authors and centuries into one model, instead of separating. Did you try and compare results?

Reply on news.ycombinator.com