Text Normalizer – Unicode Normalization Tool
Normalize text to Unicode standards (NFC, NFD, NFKC, NFKD) for consistent data storage, search optimization, and text processing.
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Text Normalizer
Default for most applications, web forms, databases
Normalization Forms
NFC
NFC
Combines characters into their composed form
Default for most applications, web forms, databases
NFD
NFD
Separates characters into base + combining marks
Text analysis, accent removal, linguistic processing
NFKC
NFKC
Normalizes compatibility characters and composes
Search engines, identifiers, case-insensitive comparison
NFKD
NFKD
Full decomposition including compatibility characters
Maximum compatibility, legacy system integration
Quick Guide
When to use NFC?
Use for web forms, databases, and general text processing. Most common and recommended form for web applications.
When to use NFD?
Use for accent removal, text analysis, and linguistic processing. Separates base characters from combining marks.
When to use NFKC?
Use for search engines, identifiers, and case-insensitive comparison. Converts compatibility characters.
When to use NFKD?
Use for maximum compatibility with legacy systems. Full decomposition including compatibility characters.
Example Texts
Examples of Real-World Usage
8 real-world examples
Database Management
Normalize text before storing in databases to ensure consistent data, accurate searches, and prevent duplicate entries with different Unicode representations.
Search Engines
Improve search accuracy by normalizing both indexed content and search queries. Ensures café, cafe, and café all match correctly.
Software Development
Normalize user input, validate identifiers, and ensure consistent text processing in applications. Essential for internationalized software.
Internationalization
Handle multilingual content correctly by normalizing text from different sources. Ensures consistent display and processing across languages.
Content Management
Standardize content from multiple authors and sources. Prevents formatting inconsistencies and ensures uniform text representation.
Data Validation
Validate and clean user input by normalizing to a standard form. Helps detect duplicate entries and ensure data quality.
Text Processing
Prepare text for analysis, translation, or transformation. NFD decomposition makes it easy to remove accents or analyze character components.
Data Migration
Normalize text when migrating between systems or databases. Ensures compatibility and prevents encoding issues during data transfer.
Key Features of Text Normalizer
Powerful Unicode normalization with all standard forms.
4 Unicode Forms
Support for NFC, NFD, NFKC, and NFKD normalization standards.
Instant Processing
Real-time normalization with live preview and statistics.
Database Ready
Normalize text for consistent database storage and queries.
Search Optimization
Improve search accuracy by normalizing text before indexing.
Change Detection
Visual indicators show when text was modified during normalization.
Export Options
Download normalized text with form type in filename.
Developer Friendly
Shows code points, byte length, and character count statistics.
Multi-Language
Works with all Unicode scripts: Latin, Cyrillic, Arabic, CJK, and more.
How to Use
Simple 4-step process
Step 1
Paste or upload your text that needs Unicode normalization.
Step 2
Select the normalization form: NFC, NFD, NFKC, or NFKD based on your needs.
Step 3
See instant preview of normalized text with statistics showing changes.
Step 4
Copy the normalized text or download it as a file for use in your application.
Frequently Asked Questions
Everything you need to know about our process, pricing, and technical capabilities.
See Full FAQUnicode normalization is the process of converting text to a standard form. Some characters can be represented in multiple ways in Unicode (e.g., é can be one character or e + combining accent). Normalization ensures consistent representation.
NFC (Canonical Composition) combines characters into their composed form (é as one character). NFD (Canonical Decomposition) separates them into base + combining marks (e + ´). NFC is more compact, NFD is better for analysis.
Use NFKC/NFKD when you need compatibility normalization. They convert similar-looking characters to a standard form (e.g., fullwidth letters to regular, ligatures to separate letters). Good for search and identifiers.
If your text is already in the selected normalization form, it won't change visually. However, the underlying Unicode representation may differ. Check the statistics to see if byte length or code points changed.
Yes! Use NFD or NFKD to decompose accented characters into base + combining marks. Then you can easily remove the combining marks to get plain text. This is more reliable than manual accent mapping.
NFC ↔ NFD is generally reversible (canonical forms). However, NFKC and NFKD are NOT reversible because they lose information (e.g., ligature fi becomes fi and can't be converted back).
Yes, it's recommended! Use NFC for most databases. This ensures consistent storage, accurate comparisons, and prevents duplicate entries that look identical but have different Unicode representations.
Yes, some emoji are composed of multiple code points (e.g., flags, skin tones). Normalization can affect how they're stored but usually doesn't change their visual appearance.
Yes, you can upload text files. The tool processes them instantly in your browser. All processing is client-side, so your data stays private.
Yes, Text Normalizer is completely free to use with no limits on text size or number of normalizations.
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