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Normalize Text

Apply Unicode normalisation so identical-looking text really matches.

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All four Unicode normalisation forms are produced below. NFC is what the web and most databases expect; NFKC and NFKD fold compatibility variants and genuinely lose information.

Quick Tool Overview

Normalize Text applies Unicode normalisation so that strings which look identical actually compare as equal. All four forms are produced side by side — NFC for storage and comparison, NFD before stripping accents, NFKC and NFKD to fold compatibility variants — with the code point counts that show what changed.

What it does
Applies Unicode NFC, NFD, NFKC and NFKD normalisation
You give it
A string that is failing a comparison or a search
You get back
All four normalised forms with their code point counts
Best for
Fixing search and comparison failures on accented text
Text Tools Free, unlimited use No sign-up Runs in your browser

About the Normalize Text

Two strings can look identical on screen and still not be equal, because Unicode often offers more than one way to write the same thing. The letter é can be a single character, or an e followed by a separate combining accent. They render the same and compare as different, which is why a search fails on text that is visibly there.

Normalisation resolves that by rewriting text into one canonical form. NFC composes characters together and is what you want for storage and comparison — it is the form the web has standardised on. NFD decomposes them, which is what macOS filesystems use and what you need before stripping accents. NFKC and NFKD go further and fold compatibility variants, so a full-width Ａ becomes a plain A and a fi ligature becomes two letters. All four are here, with a comparison showing exactly what changed.

Key features of the Normalize Text

All four forms at once

Rather than converting blind, you see what each form does to your text before choosing one.

Code point counts shown

The difference between composed and decomposed is invisible on screen but obvious in the counts.

Difference highlighted

The characters that changed are marked, so you can see exactly where the two encodings diverged.

Guidance on which to pick

The page says plainly that NFC is right for the web and NFKC loses information, so the choice is informed.

Works on any script

Accented Latin, Korean Hangul, full-width CJK forms and ligatures are all normalised correctly.

How to use the Normalize Text

  1. 1

    Paste your text

    A string that is failing a comparison, or data from a system with different conventions.

  2. 2

    Choose a normalisation form

    NFC for storage and comparison, NFD before removing accents, NFKC or NFKD to fold compatibility variants.

  3. 3

    Compare the forms

    All four results are shown with their code point counts, so the difference between them is visible.

  4. 4

    Copy the normalised text

    Copy the form you need, ready to store or compare.

Frequently asked questions

NFC for nearly everything — it is what the W3C recommends for the web and what most databases expect. Use NFD only when you need decomposed characters, typically before stripping accents or when working with macOS filenames.

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