Uncovering censorship in the 16th century with Transkribus and Python. Episode IV: Detecting OCR transcription errors

by Markus Müller

In the last episode, we built a pipeline to convert a diplomatic transcription into normalized Latin text. The code works fine as long as the diplomatic transcription is correct. But what happens if the transcription contains errors or, even worse, if the printer in the 16th century misspelled a word? – Right now, nothing would happen at the moment because our pipeline cannot detect these errors. This is a problem because as soon as we start comparing two editions of the same text to check for censorship (and that’s where we are going!), the slightest difference between the two texts may be interpreted as censorship. Can we solve this problem? – Yes, we can!

„Uncovering censorship in the 16th century with Transkribus and Python. Episode IV: Detecting OCR transcription errors“ weiterlesen

Uncovering censorship in the 16th century with Transkribus and Python. Episode III: Normalizing 16th century raw text

by Markus Müller

Visiting a museum as a kid, I sometimes wondered why I could hardly read anything in the medieval or early modern books and manuscripts displayed in the exhibition. Even after I learned Latin in school, the situation did not improve. I was not aware that people in former centuries used a lot more abbreviations than today, especially in Latin texts. As long as paper (or parchment) was very expensive, scribes and printers tried to save as much space as possible. Therefore, a sentence like “In principio fecit deus caelum et terram” could be abbreviated as “In prīcipio fecit de celū ťrā” (“In the beginning, God created the heavens and earth” — the first verse of the Bible). You may have noted that these abbreviations worked differently than abbreviations like “WWW” or “U.S.” that we are familiar with today, and it would be nice if they could be resolved automatically with a Python script.

„Uncovering censorship in the 16th century with Transkribus and Python. Episode III: Normalizing 16th century raw text“ weiterlesen