How does the normalisation work?

Text is decomposed with Unicode NFD, which splits accented characters into a base letter plus a combining mark, and then the combining marks are removed.

Are ligatures and special characters handled?

Pure diacritics are stripped (é → e). Letters that aren't decomposable, like ß or ø, are left unchanged because they don't have a base + accent form.

Is the input ever uploaded?

No. The normalisation runs in your browser using the built-in String.normalize routine.

NFD normalize · diacritic strip · ASCII

Remove accents & diacritics

Strip diacritical marks (é, ñ, ü, å) to their ASCII base letters. Useful for slugs, IDs, and search indexes.

Remove Accents Workspace

Input size

56 B

with accents

Output size

56 B

stripped

Diff

marks removed

Normalize

NFD

Unicode aware

input · with accents

output · ASCII-folded

cafe naive jalapeno resume creme brulee Zurich Sao Paulo

Quick Start

How to strip accents

Unicode normalization form D (NFD) decomposes accented characters into base + combining mark, then the combining marks are stripped.

01
Paste text
Any text with diacritics.
Tokenisation is Unicode-aware via \p{L}\p{N} property classes — so accented letters, ideographs, and emoji code points all count correctly.
any textUTF-8Unicodecode pointslive
input · textcafé · UTF-8
```
café résumé
```
loaded · UTF-8UTF-8 · ready
02
NFD normalize
é → e + ́ (combining acute). Then the combining mark is stripped.
Live re-counts run on every keystroke through a memoised reducer, so even multi-megabyte inputs stay smooth in the editor.
NFDlivememoisedoptionssnappy
step · optionsdecompose · live
```
e + ́  →  e
```
options applied · livelive
03
ASCII output
Base letters remain; non-decomposable characters (Chinese, Arabic) are untouched.
Output preserves the original line endings (\n vs \r\n) and trailing whitespace is reported separately so you can spot diff-only changes.
ASCIIline endingswhitespacediff-cleanreproducible
output · countedASCII · ready
```
cafe resume
```
counted · livecounted
04
Copy or download
One click.
Copy writes via the Async Clipboard API; downloads ship as text/plain; charset=utf-8 — nothing leaves your tab.
copyclipboardtext/plainblobclient-side
export · copiedready · done
```
✓ Copied
```
shipped · ready to shipsuccess

Pro tips

Text-processing fundamentals worth knowing

Tokenise with Unicode classes

Use \p{L}\p{N} with the u flag so accents, ideographs, and emoji count properly.

Normalise line endings

Convert \r\n to \n before diffing or hashing — Windows-vs-Unix endings produce phantom changes.

Mind invisible characters

Zero-width joiners, BOMs, and non-breaking spaces look identical to ASCII space. Strip them before comparison or storage.

Stream don’t slurp

For multi-megabyte text, iterate line-by-line rather than loading everything to memory — keeps the tab responsive.

Choose collation deliberately

Default JS sort is code-point order, not human alphabetical. Use Intl.Collator for locale-aware sorting.

Re-run after normalisation

NFC vs NFD changes byte length but not visible glyphs. String.prototype.normalize() before counts and comparisons.

Use Cases

When to remove accents

Anywhere ASCII-only input is required.

URL slugs

café → cafe before generating a URL. Tokenisation uses Unicode property classes (\p{L}, \p{N}) with the u flag so accents, ideographs, and emoji code points all count correctly. Surrogate-pair-aware counts mean 🚀 weighs 1, not 2.

Unicode-correct

Search indexes

Strip accents in queries so résumé matches resume. Result updates as you type — paste and watch totals settle in milliseconds even on multi-megabyte inputs. Heavy work runs through a memoised reducer so the editor never janks.

diff-clean

Filenames

ASCII filenames for cross-OS compatibility. Output normalises line endings to LF for clean diffs across platforms. Windows-vs-Unix CRLF mismatches disappear, which keeps git blame honest and review comments focused on real changes.

instant counts

Legacy systems

ASCII-only databases or APIs. Code-point counts are stable across NFC/NFD normalisation. Pair with the Reading Time Calculator to layer scan-time on top of raw counts, useful for editorial budgets and SEO meta-description limits.

platform-aware

Username normalize

Compare 'José' and 'Jose' as equivalent. All processing runs client-side — paste sensitive or pre-publish copy without it leaving the tab. The clipboard API writes UTF-8 text/plain so it survives transit to any editor or CMS.

code-point-accurate

Subdomain generation

DNS doesn't allow accented chars. Same input plus same options always produces identical output, so the tool is safe to embed in CI scripts or doc-generation pipelines without race conditions.

lossless

FAQ

Frequently asked questions

What's NFD normalization?

Unicode Normalization Form D — Canonical Decomposition. Splits a composed character (é) into base (e) + combining mark (́).

Does it handle non-Latin scripts?

Most Latin diacritics work. Non-decomposable scripts (Chinese, Arabic) pass through unchanged.

What about ß or æ?

These aren't accents — they're separate letters. Use a transliteration library for ß → ss or æ → ae.

Is it idempotent?

Yes — running twice produces the same result.

Is anything sent to a server?

No. All processing runs locally.

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