Professional Transcription of Old German Handwritten Documents

At the end of every calendar year, I set aside an entire day to test the current generation of machine and AI solutions specifically for transcribing German Kurrent script. I try all models available on the market (always in their paid versions, with full functionality enabled). I measure the error rate, the time it takes to upload, process and organise the results, and, most importantly, the time and effort required to compare everything with the original manuscript and correct the errors.

Test results from November 2025

On the same sample text, written in a fairly neat and not particularly difficult hand, the available solutions (and here I only count those that actually recognise text rather than hallucinate it) produced between 3% and 16% incorrectly recognised words, including both grammatical distortions and completely wrong readings. In practice, this means false entries in every third to every single line of the manuscript. This significantly distorts the overall meaning and makes the material, in that raw form, barely suitable even for machine translation: while errors in function words can often be corrected manually or with AI, the appearance of words or clusters of letters that are not in the original document at all inevitably leads to false interpretations of the facts of the case.

In the end, my “test drive” showed the following: the time needed to process and correct the output of an automatic transcription of a simple hand – including detecting and fixing all errors – is roughly the same as the time I spend transcribing the very same text manually (and I type quite fast, touch-typing and without looking at the keyboard).

Pros and cons

Training your own model to get even better results? This can make sense if you are dealing with a very large set of documents all written by the same person. In archival files, however, you usually encounter such a patchwork of different hands that within one file you will have pages on which a custom-trained model performs very well (with only a few percent of errors) and others on which more than half of the words are misrecognised. At least, that has been my experience: the time invested in training a model for a specific corpus (say, a few dozen or even a couple of hundred pages) exceeds the time it would take to transcribe them manually – and you still cannot avoid checking and correcting the results afterwards.

When you transcribe line by line, it is crucial to keep the overall context and argument of the document in view. Current machine models are not yet capable of this. And if you add an additional AI “post-processing” step on top of the machine transcription, the AI starts hallucinating: it arbitrarily replaces words with similar ones and invents things that were never in the original document. If you do not read Kurrent yourself, there is simply no way to reliably detect such surprises.

You also have to take into account the specific ways in which personal names, place names, obsolete terms and dialect forms appear in an old manuscript created in a particular region. At a genuinely professional level, all these tasks can, for the time being, only be handled by a real human being who has mastered the art of reading old German scripts.

And finally, professional transcription is indispensable if you plan, now or later, to publish anything based on the transcribed documents.

So here is my answer and recommendation —

yes, you can use AI if:

• you yourself have a sufficiently confident command of German (ideally you can read Kurrent, even if slowly) to critically review the machine output;
• you have made sure that you are uploading your documents into a tool that recognises actual text rather than inventing it;
• you have the time and patience to compare the result word by word with the manuscript and correct it;
• you are transcribing only a modest amount of text;
• or you simply need a general idea of the content and type of the document, accepting a likely loss of detail and of the authentic texture of the file.

If, however, you do not have that much free time and stamina, or if you need:

• a transcription of a longer text or an entire archival file consisting of many pages;
• a transcription in which nothing has been made up;
• a transcription you are not embarrassed to quote, because it is accurate, free of lexical distortions and semantic hallucinations, and all grammatical and orthographic fluctuations reflect the linguistic norms of the period in which the document was created, or the author’s individual style;
• a transcription that you can confidently use for publication, whether in a blog, an academic paper or a journal;

— and especially if you have already spent time, nerves and perhaps money experimenting with machine and AI tools, only to conclude that your particular documents require expert manual work —

then I will gladly take this burden off your shoulders and work carefully through your documents for you.