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The reliable way to convert Traditional Chinese in a PDF is to treat it as three separate jobs: recover the document’s text, run OCR on pages that are only images, and convert the recovered Chinese with a script-and-vocabulary tool such as OpenCC. A PDF may contain born-digital text, scanned images, or a mixture, so one operation cannot safely handle every file. After conversion, inspect the text and decide separately whether you need a new searchable PDF or only a converted text file.
Why PDF conversion needs a combined approach
“PDF” describes a container, not the way its pages were created. A digitally generated page normally has a text layer that applications can select and copy. A scanned page may contain nothing but a raster image. A long document can also mix the two: a typed cover, image-only chapters, and digitally generated appendices.
Those input types require different operations. A text extractor can recover characters that are already encoded in the file, but it cannot read pixels on an image-only page. OCR can recognize characters in pixels, but it may introduce recognition errors and does not, by itself, change Traditional Chinese into Simplified Chinese. OpenCC performs the script and regional-wording conversion after text has been recovered.
This is a practical workflow inference from the documented capabilities of OCRmyPDF, Tesseract and OpenCC, not a claim that one universal pipeline preserves every layout or achieves a fixed accuracy. No published accuracy or speed benchmark for this exact end-to-end combination is established here.
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First, identify what kind of PDF you have
Born-digital pages with a usable text layer
Try selecting a sentence with the mouse and pasting it into a plain-text editor. If Chinese characters appear in the pasted result, the page probably has extractable text. Run a text extractor across the complete file rather than assuming that a visual selection test represents every page.
pdftotext -layout input.pdf extracted.txtPoppler’s pdftotext and pdfgrep are examples of programs OCRmyPDF recommends for extracting all text from a PDF, whether that text came from OCR or was present originally. The -layout option attempts to retain spacing; it does not guarantee that columns, tables or captions will read in their original visual order.
Scanned or image-only pages
If copying produces nothing, produces a single image, or returns empty text for particular pages, those pages need OCR. A PDF viewer may display a perfectly legible scan while still offering no searchable characters.
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Mixed PDFs
Mixed files are the reason a single “OCR everything” shortcut can be misleading. OCRmyPDF can add a searchable layer to scanned pages while leaving pages that already contain text in place. To discover the complete document text, still run a PDF text extractor after processing. OCRmyPDF’s sidecar output is OCR output; pages that already had a text layer are omitted from that sidecar, so the sidecar alone is not a complete transcription of a mixed PDF.
Step 1: extract existing text before OCR
- Make a working copy. Keep the original PDF unchanged so you can compare pages and rerun a different language or conversion configuration.
- Extract all available text. Use
pdftotext(or search withpdfgrep) and save the result as a separate file. - Check the output by page. Look for blank ranges, garbled characters, missing punctuation, or text that appears in the wrong column order. Those symptoms identify pages that need OCR or manual review.
- Record the source variety. A Taiwan, Hong Kong or general Traditional Chinese document may require a different OpenCC configuration later. Do not choose a conversion profile solely from the file name.
Example search command:
pdfgrep -n "關鍵字" input.pdfIf the search finds only some occurrences, that is evidence of a mixed or incomplete text layer, not proof that the missing words are absent from the page images.
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Step 2: OCR pages that lack usable text
OCRmyPDF uses Tesseract language packs to recognize scanned pages and add a searchable text layer. Its documentation gives chi_sim as the Simplified Chinese language-pack example and supports requesting multiple languages. OCR language selection matters: choosing only English for a Chinese scan can turn characters into meaningless Latin letters even when the page is sharp.
A typical command, assuming OCRmyPDF and the required Tesseract language data are installed, is:
ocrmypdf -l chi_sim input.pdf searchable.pdfFor a document that includes Chinese and English, request both languages:
ocrmypdf -l chi_sim+eng input.pdf searchable-bilingual.pdfThese commands create a searchable PDF; they do not convert Traditional characters into Simplified characters. If your source scan is Traditional Chinese, the OCR language choice and the later OpenCC conversion are separate decisions. Use the language data appropriate to what is printed on the page, then convert the resulting text.
Using a sidecar without losing born-digital text
OCRmyPDF can write OCR text to a sidecar file. That file is useful for pages OCR actually processed, but it is not a guaranteed full-document export because pages that already had text are left out. For a complete result, extract text from the resulting PDF with pdftotext, then compare it with any sidecar used for OCR checking.
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What to inspect after OCR
- Characters that look similar, especially punctuation, numerals and uncommon Chinese glyphs.
- Reading order in two-column pages, tables, footnotes and vertical text.
- Headers, page numbers and watermarks accidentally inserted into body text.
- Names, addresses, product codes and specialist terms, where one OCR error can change the meaning.
- Pages with faint print, skew, seals, handwriting or complex backgrounds.
OCR recognition quality depends on the scan and language data. The available documentation does not provide a benchmark that would let you promise a particular error rate for your PDF.
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OpenCC is designed for Chinese character and regional-usage conversion. It supports character-level and phrase-level mappings, variant handling and regional vocabulary. That matters because Traditional-to-Simplified work is not always a glyph-for-glyph substitution: a phrase that is natural in Taiwan or Hong Kong may require a different Mainland China expression even after the characters are simplified.
Choose the configuration from source and target
| Source and intended output | OpenCC configuration | What it addresses |
|---|---|---|
| General Traditional Chinese to standard Simplified Chinese | t2s |
Traditional-to-Simplified character conversion with OpenCC’s standard mapping. |
| Taiwan Traditional Chinese to Simplified Chinese using Mainland China wording | tw2sp |
Character conversion plus phrase choices aimed at Mainland China usage. |
| Hong Kong or Taiwan variants where the target wording is not standard Mainland usage | Use the corresponding regional configuration supplied with OpenCC. | Preserves the distinction between regional variants instead of forcing every document through one profile. |
The configuration names describe conversion direction and regional vocabulary; they do not mean that OpenCC translates Mandarin, Cantonese or another spoken language. If the reader needs a translation rather than a script change, a separate translation process and human review are required.
Convert an extracted text file
With OpenCC’s command-line interface and configuration files available, a basic conversion can look like this:
opencc -c t2s.json -i extracted.txt -o simplified.txtFor Taiwan Traditional text intended to read with Mainland China phrases, use the matching configuration:
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opencc -c tw2sp.json -i extracted.txt -o simplified-mainland.txtKeep the Traditional source and the Simplified output as separate files. That makes it possible to audit a questionable name or term and to rerun the conversion with a different regional configuration without repeating OCR.
Review phrase changes, not only individual characters
OpenCC’s phrase-level mappings can alter wording that a simple character table would leave untouched. Review personal names, place names, legal language, medical terminology, software strings and organization names against the original page. A phrase conversion can be linguistically appropriate for the selected region and still be wrong for a brand name or a quoted title that should remain unchanged.
Step 4: decide what the final deliverable is
When plain text is enough
If the goal is search, indexing, analysis or copying into another application, deliver the OpenCC-converted text file. This avoids promising that a newly built PDF will look exactly like the source.
When you need a searchable PDF
Retain the OCRmyPDF output when you need the original pages to remain visually recognizable with a searchable layer. In that case, the searchable layer may still contain Traditional characters unless you replace it with converted text through a separate PDF-production step. OCRmyPDF and OpenCC provide distinct capabilities; neither documentation establishes a single command that converts the script while preserving every original text position.
When visual reformatting is required
A PDF whose visible text must change from Traditional to Simplified may need to be rebuilt or edited in a layout-aware application. Treat visual fidelity as a separate requirement. Check line breaks, font coverage, text direction, tables, annotations, bookmarks and page numbers after rebuilding. A converted text file can be correct even when a visually reconstructed PDF needs additional typesetting work.
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Choose the route that matches your PDF
| PDF condition | First operation | Then convert | Best initial output |
|---|---|---|---|
| All pages have selectable Chinese text | pdftotext |
OpenCC t2s or an appropriate regional profile |
Converted text; rebuild a PDF only if layout is required. |
| All pages are scans | OCRmyPDF with the source-language Tesseract pack | Extract the OCR result, then run OpenCC | Searchable OCR PDF plus a reviewed converted text file. |
| Some pages are text and others are scans | Extract first, OCR missing pages, then extract the resulting PDF again | Run OpenCC on the complete extraction | A complete text export; preserve the OCR PDF separately. |
| Taiwan or Hong Kong source with Mainland-target wording | Text extraction and/or OCR as above | Select the matching regional OpenCC configuration, such as tw2sp for Taiwan-to-Mainland use |
Converted text with names and specialist terms manually checked. |
Windows 11 workflow and checkpoints
On Windows 11, run the commands in a terminal where the relevant programs and language data are installed. The exact installation route depends on whether you use a native build, a Linux environment or another managed setup, so verify each executable before processing a valuable file.
- Copy the original PDF into a project folder and create a separate output folder.
- Run
pdftotextand open the result. Note page ranges that are blank or unusable. - Run OCRmyPDF on the original or a working copy, selecting the language printed on the scan. Add
engwhen English appears alongside Chinese. - Run
pdftotexton the OCRmyPDF output to obtain one complete extraction. Do not rely only on an OCR sidecar for a mixed PDF. - Run OpenCC with
t2sfor general Traditional-to-Simplified conversion, or a regional profile such astw2spwhen Mainland China vocabulary is the target. - Compare a sample from the beginning, middle and end with the original pages. Include tables, captions, names and pages that previously failed extraction.
- Deliver the converted text, the searchable OCR PDF and the untouched original as clearly named files if recipients may need both content and visual reference.
Common failure modes and fixes
The output file is empty
The PDF may be image-only, encrypted, damaged or made with an unusual text encoding. Confirm that the viewer permits copying, then OCR the affected pages and extract text from the OCR result.
Only part of the document appears in the sidecar
This is expected when some pages already had text. Use pdftotext on the complete PDF instead; the sidecar is not a substitute for a full-document extraction.
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Chinese characters become Latin gibberish during OCR
Check the Tesseract language selection and install the appropriate language data. Use the language printed on the source page, not the script you want as the final output. Script conversion happens later with OpenCC.
Characters are simplified but wording still sounds regional
Use the OpenCC configuration that matches both source region and target wording. Standard t2s and a Taiwan-to-Mainland profile such as tw2sp are not interchangeable goals.
The converted PDF has broken layout
Separate content conversion from visual reconstruction. Keep the OCR PDF as a searchable reference, then rebuild only the pages whose visible Simplified text is required. Inspect line wrapping, fonts, columns and tables rather than assuming that a text conversion will preserve coordinates.
Names or technical terms changed unexpectedly
Compare the converted text with the original image or text layer. OpenCC’s phrase and regional mappings are useful for ordinary language but cannot know every proprietary name, quotation or domain-specific exception. Maintain a review list and correct those items manually.
Quality-control checklist before sharing
- Every page has either extractable text or a documented OCR result.
- The extraction includes pages that were born digital as well as pages OCR processed.
- The OCR language matches the printed source language, with additional languages requested when needed.
- The OpenCC configuration matches the source variety and desired target vocabulary.
- Names, numbers, URLs, tables, headings and specialist terms were checked against the original.
- You have stated whether the deliverable is converted text, a searchable PDF, or a visually rebuilt PDF.
- The original file remains available for dispute resolution and later reprocessing.
What this workflow can and cannot promise
It can separate text recovery, image recognition and Chinese script or regional-wording conversion so that each problem is handled by a tool designed for it. It cannot guarantee perfect OCR, automatic treatment of every proper name, or complete preservation of PDF layout after visible text is changed. The safest practice is to preserve the original, retain the searchable OCR version, keep the converted text separately, and inspect the pages and terms that matter most.
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