What this converter can do
- Fullwidth ↔ halfwidth for ASCII letters, numbers, and symbols.
- Hiragana ↔ Katakana and Katakana full ↔ half width.
- Optional space normalization that respects line breaks.
- Auto-converts as you type, with one-click copy for results.
Convert instantly
Clean up Japanese text
Paste text, pick a conversion type, and see the result update automatically. No data leaves your browser.
Switch between kana or width styles without reformatting the rest of your text.
Preview
Notes on zenkaku / hankaku conversion
“Fullwidth” and “halfwidth” are presentation forms used often in Japanese text. This tool helps you normalize input for forms, labels, and test data—but exact behavior can differ across systems.
Halfwidth katakana (ｶﾀｶﾅ) and dakuten
- Some halfwidth katakana with diacritics can be represented as two characters (e.g., “ｶ” + “ﾞ” for “ｶﾞ”). Converting may change string length.
- If you paste into fixed-width fields, validate the final result in the target system.
Spaces and alignment
- Normalize spaces collapses repeated spaces and tabs per line (including fullwidth spaces) while keeping line breaks.
- This is helpful for cleanup, but it may remove intentional alignment/indentation.
Symbols that may not convert
Not every punctuation mark has a fullwidth/halfwidth counterpart. Characters without a clear mapping are left unchanged.
References
Zenkaku/Hankaku conversion workflow for production text
Use this converter as a normalization step in your text pipeline, not as a final proofreading step. Width conversion, kana conversion, and space normalization each solve different problems. Width conversion aligns ASCII-compatible systems, kana conversion aligns reading style, and space normalization stabilizes copy/paste behavior. Decide which operations are mandatory for your destination format before applying all toggles. This avoids accidental changes to user names, IDs, or punctuation that must stay exactly as entered.
Practical sequence
- Start from a clean source and keep one untouched backup copy.
- Apply width conversion first for digits/symbols if the target system expects halfwidth.
- Apply kana conversion only when your content policy requires Hiragana or Katakana consistency.
- Run space normalization last to stabilize TSV/CSV or fixed-format exports.
Common mistakes to avoid
- Converting legal names or account identifiers that must preserve original glyph width.
- Applying kana conversion blindly in mixed-language content.
- Forgetting to revalidate delimiters before importing into spreadsheets or databases.
Mini QA example
A support team receives customer lists where phone numbers include fullwidth digits and comments include mixed kana. Convert digits/symbols to halfwidth, keep kana untouched for names, then normalize spaces for stable column imports. Validate a 20-row sample in the destination sheet before bulk processing. This sequence prevents field split errors while preserving user-visible wording.
See also
- Text case converter for casing normalization after width cleanup.
- JSON formatter & validator for structured text QA.
- Random picker to sample rows for manual audits.
- Timer for repeatable review sessions.
How to use this tool effectively
This guide helps you use Zenkaku / Hankaku Converter in a repeatable way: define a baseline, change one variable at a time, and interpret outputs with explicit assumptions before you share or act on results.
How it works
The page applies deterministic logic to your inputs and shows rounded output for readability. Treat it as a comparison workflow: run one baseline case, adjust a single parameter, and measure both absolute and percentage deltas. If a result seems off, verify units, time basis, and sign conventions before drawing conclusions. This approach keeps your analysis reproducible across teammates and sessions.
When to use
Use this page when you need a fast estimate, a classroom check, or a practical what-if comparison. It works best for planning and prioritization steps where you need direction and magnitude quickly before investing in deeper modeling, manual spreadsheets, or formal external review.
Common mistakes to avoid
- Changing multiple parameters at once, which hides the true cause of output movement.
- Mixing units (percent vs decimal, monthly vs yearly, gross vs net) across scenarios.
- Comparing with another tool without aligning defaults, constants, and rounding rules.
- Using rounded display values as exact downstream inputs without re-checking precision.
Interpretation and worked example
Run a baseline scenario and keep that result visible. Next, modify one assumption to reflect your realistic alternative and compare direction plus size of change. If the direction matches your domain expectation and the size is plausible, your setup is usually coherent. If not, check hidden defaults, boundary conditions, and interpretation notes before deciding which scenario to adopt.
See also
Frequently asked questions
Does the text leave my browser?
No. All conversions run locally, so pasted names or drafts never leave your device.
What does Normalize spaces do?
It collapses repeated spaces and tabs (including fullwidth spaces) into single spaces per line, keeping line breaks while cleaning extra spacing.
What is the difference between kana conversion and width conversion?
Kana conversion changes script style (Hiragana/Katakana), while width conversion changes character width (fullwidth/halfwidth). They are independent operations.
Will punctuation and numbers also be converted?
Yes, when width conversion is enabled. Fullwidth symbols and digits can be converted to halfwidth forms for system compatibility.
How can I avoid breaking CSV or TSV imports?
Run a small sample export after conversion, verify delimiters and quotes, then apply the same settings to the full dataset.