How does café become cafe exactly?

The accented é is one Unicode code point, but NFD normalization splits it into a plain e plus a separate combining acute accent (U+0301). The tool then deletes every combining mark in the U+0300 to U+036F range, leaving the bare e, so café turns into cafe. The same path turns naïve into naive and Müller into Muller, because the dieresis and umlaut are combining marks too.

Why does ñ turn into n but Chinese text stays the same?

ñ is a Latin n carrying a combining tilde, so once NFD splits it the tilde is dropped and you are left with n. Chinese, Japanese, Korean and Arabic characters are not Latin letters with stackable accents, they are distinct code points with no combining marks to remove, so the tool passes them through unchanged. Mixing 北京 café in one line gives back 北京 cafe.

Why is German ß handled separately as ss?

Letters like ß, ø, ł, đ and the ligatures æ, œ, þ do not decompose under NFD because they are not a base letter plus an accent, they are their own glyphs. So the tool keeps a small map: ß becomes ss, ø becomes o, ł becomes l, æ becomes ae, œ becomes oe, þ becomes th, including the capital forms. Toggle the option off if you would rather leave these letters as they are.

What is this good for in real work?

Anywhere a system only accepts ASCII. URL slugs from a title like Crème Brûlée become creme-brulee, search keys match whether the user typed resume or résumé, filenames stop breaking on older systems, and CSV or database imports stop throwing encoding errors. It is also handy before sorting, because accented letters sort unpredictably across locales.

Does removing accents change the pronunciation or meaning?

It can. Stripping accents is a lossy operation: French résumé and resume collapse to the same spelling, and a diacritic that distinguishes two words in a language is lost. For display text meant for human reading, keep the accents. Use this tool only for the machine facing layer, slugs, keys, identifiers, where ASCII is required and the original text still lives elsewhere.

Is my text uploaded anywhere?

No. Every step runs as plain JavaScript inside your browser tab, so the text you paste never reaches a server and is never logged. The one caveat is the share link, which encodes your input in the URL, so a link pasted into chat will record that text in the recipient server access log. For anything sensitive, use the copy button and paste the result instead of sharing the URL.

Generate clean URL slugs from accented titles

A blog post titled Crème Brûlée Recipe or a product named Açaí Bowl needs a URL that every browser, CDN and analytics tool handles the same way. Strip the accents first to get creme-brulee-recipe and acai-bowl, then hand off to your slug step. ASCII slugs avoid the percent-encoding mess that accented URLs turn into when copied and pasted, and they stay readable in a shared link.

Build a search index that ignores accents

Your users type resume when the database stored résumé, or Munchen for München. Normalize both the stored field and the query through this tool and the two finally match. Search becomes accent insensitive without a fragile per language rule set, which is exactly what people expect from a forgiving search box.

Fix filenames before a batch upload

Older file systems, ZIP tools and some CI pipelines mangle accented filenames into garbage like Cafe%CC%81.jpg. Run the names through the tool first so résumé.pdf becomes resume.pdf and über_plan.xlsx becomes uber_plan.xlsx, and the upload, the download and the link all agree on one safe spelling.

Clean a CSV or data export for import

A spreadsheet of European customer names full of ñ, é, ü and ø can break a strict ASCII importer or a legacy database column. Paste the column, remove the accents, and paste the cleaned values back so the import stops throwing encoding errors, while you keep the original accented file as the source of truth.

Remove Accents: Strip Diacritics to Plain ASCII

Strip diacritics from Latin text, café to cafe, ñ to n, ß to ss, runs entirely in your browser

Runs locally
Category Text
Best for Removing repetitive cleanup work from everyday writing and operations.

Also convert ø ł đ ß æ œ þLetters NFD cannot split (German ß → ss, Nordic ø → o, Polish ł → l)

Input — one or many lines

Result

What this tool does

Free online tool to remove accents and diacritics from text and turn café into cafe, naïve into naive, Müller into Muller. It NFD-normalizes every character, drops the combining marks (grave, acute, circumflex, tilde, umlaut, cedilla and the rest), then recomposes the result as plain ASCII letters. A second pass handles the awkward letters that Unicode cannot split apart on its own, so German ß becomes ss, Nordic ø becomes o, Polish ł becomes l, and the ligatures æ, œ, þ expand to ae, oe and th. You decide whether those special letters get transliterated or kept. Non Latin scripts like Chinese, Japanese, Korean and Arabic are never touched, and emoji survive intact. Paste one line or a thousand, get a one click copy, and share a link that reopens your exact text. Useful for slugs, search keys, filenames, CSV cleanup and any system that chokes on accented characters. 100% client side, nothing is uploaded.

Tool details

Input: Files + Text; The page exposes text boxes, numeric controls, file pickers, or structured inputs depending on the tool.
Output: Live result + Copy; The result area focuses on usable output, with copy, download, or preview actions when supported.
Privacy: Browser-side processing; The main tool logic does not call an external API, so inputs normally stay in the current tab.
Save / share: Shareable URL state; Key settings are encoded in the URL so another person can reopen the same setup.
Performance budget: Initial JS <= 9 KB; No WASM budget is declared, keeping the tool quick to open on mobile.
Best fit: Text · Developer; Category and role tags drive related tools, internal links, and quick fit checks.

How to use

1. Input

Paste or drop your content into the tool panel.
2. Process

Click the button. All processing is local in your browser.
3. Copy / Download

Copy the result or download to disk in one click.

How Remove Accents fits into your work

Use it to clean, compare, reshape, or extract plain text before it goes into a document, CMS, spreadsheet, or prompt.

Text jobs

Removing repetitive cleanup work from everyday writing and operations.
Making text easier to compare, paste, publish, or feed into another tool.
Working with content locally when the text is private or unfinished.

Text checks

Scan for unintended whitespace, duplicate lines, and lost punctuation.
For long text, test the first few lines before applying the whole change.
Copy the final output only after checking the preview.

Good next steps

These links move the current task into a more complete workflow.

Real-world use cases

Generate clean URL slugs from accented titles
A blog post titled Crème Brûlée Recipe or a product named Açaí Bowl needs a URL that every browser, CDN and analytics tool handles the same way. Strip the accents first to get creme-brulee-recipe and acai-bowl, then hand off to your slug step. ASCII slugs avoid the percent-encoding mess that accented URLs turn into when copied and pasted, and they stay readable in a shared link.
Build a search index that ignores accents
Your users type resume when the database stored résumé, or Munchen for München. Normalize both the stored field and the query through this tool and the two finally match. Search becomes accent insensitive without a fragile per language rule set, which is exactly what people expect from a forgiving search box.
Fix filenames before a batch upload
Older file systems, ZIP tools and some CI pipelines mangle accented filenames into garbage like Cafe%CC%81.jpg. Run the names through the tool first so résumé.pdf becomes resume.pdf and über_plan.xlsx becomes uber_plan.xlsx, and the upload, the download and the link all agree on one safe spelling.
Clean a CSV or data export for import
A spreadsheet of European customer names full of ñ, é, ü and ø can break a strict ASCII importer or a legacy database column. Paste the column, remove the accents, and paste the cleaned values back so the import stops throwing encoding errors, while you keep the original accented file as the source of truth.

Common pitfalls

Using this on display text meant for humans. Stripping accents is lossy and can change meaning, so résumé and resume collapse to one spelling. Keep accents in anything a person reads, and use this only for slugs, keys and other machine facing fields.
Forgetting that ß, ø, ł, æ are not plain accents. NFD alone leaves them untouched, so straße would stay straße. Keep the special letters option on (the default) when you need full ASCII output, otherwise these letters slip through.
Expecting it to transliterate non Latin scripts. It deliberately leaves Chinese, Japanese, Korean and Arabic alone because they have no accents to drop. If you need 北京 to become Beijing you want a romanization tool, not an accent remover.

Privacy

Every step, the NFD normalization, the combining mark removal and the special letter map, runs as plain JavaScript inside your browser tab. The text you paste never leaves the page and is never logged. The one caveat: the shareable link encodes your input in the URL query string, so a link pasted into chat will record that text in the recipient server access log. For anything sensitive, use the copy button and paste the result rather than sharing the URL.

FAQ

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Remove Accents: Strip Diacritics to Plain ASCII

What this tool does

Tool details

How to use

1. Input

2. Process

3. Copy / Download

How Remove Accents fits into your work

Text jobs

Text checks

Good next steps

Real-world use cases

Generate clean URL slugs from accented titles

Build a search index that ignores accents

Fix filenames before a batch upload

Clean a CSV or data export for import

Common pitfalls

Privacy

FAQ

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