How to OCR a PDF in Another Language

You run OCR on a French contract and get back gibberish — accented characters mangled, words that don't exist, é rendered as 6. The scan looked fine. The engine works. So what happened?

Almost always, the language was set to English.

The language setting isn't a cosmetic preference. It fundamentally changes how the recognition engine interprets the shapes on your page — and getting it wrong is one of the most common causes of bad OCR results.

Why the language setting matters so much

OCR doesn't just match shapes to letters. It uses the language to make educated guesses, and it does that in three ways:

• The alphabet. An engine set to English isn't looking for é, ñ, ü, ł, or ß. It sees those shapes and forces them into the closest ASCII letter it knows — which is why accented text comes back mutilated. For a non-Latin script (Russian, Arabic, Japanese, Chinese, Korean, Hindi), an English setting is hopeless: it's looking for the wrong characters entirely.

• The dictionary. OCR uses word knowledge to resolve ambiguous shapes. If a blurry word could be arrive or amve, an English dictionary picks arrive. Point that same dictionary at French and it will "correct" perfectly good French words into English nonsense.

• Character frequency. Languages have different letter patterns, and the engine uses them to break ties. The wrong language means the wrong assumptions.

So the wrong setting doesn't just fail to help — it actively makes things worse by confidently guessing wrong.

The steps

1. Open Blackpdf's OCR PDF tool and drop your scanned file in.

2. Select the language of the document — not your own language, and not the language of the interface. The language printed on the page.

   Supported languages include English, French, German, Spanish, Italian, Portuguese, Dutch, Polish, Russian, Japanese, Chinese (Simplified), Chinese (Traditional), Korean, Arabic, and Hindi.

3. Click Start OCR.

4. Check the result — search for a word with an accent or a language-specific character. If those came through correctly, the setting was right.

Non-Latin scripts need more from the scan

If your document is in Russian, Arabic, Japanese, Chinese, Korean, or Hindi, the language setting is non-negotiable — but image quality matters even more than usual:

• Chinese and Japanese characters are dense and detailed. A character with fifteen strokes needs enough resolution for those strokes to be distinguishable; at low resolution they merge into a blob and recognition collapses.
• Arabic is cursive and connected, with letters changing shape depending on their position in a word. It's genuinely harder to recognise than Latin script, and it's unforgiving of a poor scan.
• Devanagari (Hindi) hangs characters from a connecting headline, which a blurry or shadowed scan can break.

The practical implication: for non-Latin scripts, always enhance the scan first. Raising contrast and flattening shadows matters far more here than on a clean English page.

What about a multilingual document?

This is the case with no perfect answer. A contract with English and Spanish in parallel columns, or a paper with a foreign-language abstract, has to be recognised with one language setting per pass.

Your options:

• Choose the dominant language. If the document is 90% German with a few English words scattered through, run it as German. The English words will mostly come through anyway — they use the same alphabet.
• Split the document. If the languages are cleanly separated by page — say, an English contract followed by its French translation — split the PDF, OCR each part with its own language, then merge them back. This is the highest-accuracy route.
• Accept the mixed result. For a document you just need to be roughly searchable, the dominant language is usually good enough.

The split-and-merge route is worth the extra minute whenever the document matters — particularly if the second language uses a different script.

Common questions

I ran OCR in English on a French document. Can I redo it?

Yes. Go back to the original scan, not the OCR'd output, and run it again with the correct language. Re-running OCR on a bad text layer doesn't fix it — the engine needs to re-read the image.

All my accented characters are wrong.

Classic wrong-language symptom. The engine wasn't looking for é, à, or ç, so it substituted the nearest letter it was expecting. Re-run with the correct language.

Does the language setting affect speed?

Not meaningfully. It changes which character set and dictionary the engine loads, not how hard it works. There's no reason to leave it on English "to be faster."

My document is in a language that isn't on the list.

The supported set covers the most widely used scripts and languages. For an unsupported language written in the Latin alphabet, choosing a related language (one that shares the accented characters) often gives usable results — it's a compromise, but far better than English.

Will the right language fix a bad scan?

No. Language and image quality are two separate levers, and you need both. A perfect language setting on a shadowed, low-contrast phone photo still gives poor results — see cleaning up a scan before OCR.

Wrap-up

1. Set the language to what's printed on the page — this is the single most impactful OCR setting.
2. For non-Latin scripts, enhance the scan first; those characters need the resolution and contrast.
3. For multilingual documents, split by language, OCR each part, and merge back.
4. Verify by searching for an accented or script-specific word.

The wrong language doesn't just fail — it guesses wrong with confidence. For the basics of making a scan searchable, see extracting text from a scanned PDF.