Convert numbers ↔ words
Bidirectional: 1234.56 ⇄ 'one thousand two hundred thirty-four point five six'. Handles integers, decimals, negatives.
one thousand two hundred thirty-four point five six
How to convert numbers
Splits the integer into 1000-groups, names each group, then appends scale (thousand, million, …). Reverse parses tokens back into a number.
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Pick direction
Number→Words or Words→Number. Toggle as needed.
Tokenisation is Unicode-aware via
\p{L}\p{N}property classes — so accented letters, ideographs, and emoji code points all count correctly.modeUTF-8Unicodecode pointslivedir · text→ · UTF-8num → words
loaded · UTF-8UTF-8 · ready - 02
Type input
'1234.56' or 'one thousand two hundred…'. Negatives prefixed with -, decimals with a dot.
Live re-counts run on every keystroke through a memoised reducer, so even multi-megabyte inputs stay smooth in the editor.
inputlivememoisedoptionssnappysrc · optionsraw · live1234.56
options applied · livelive - 03
Live result
Output updates as you type. Invalid input shows '(cannot parse)'.
Output preserves the original line endings (
\nvs\r\n) and trailing whitespace is reported separately so you can spot diff-only changes.liveline endingswhitespacediff-cleanreproducibleout · countedlive · readyone thousand…
counted · livecounted - 04
Copy result
One click to clipboard for use in receipts, contracts, accessibility text.
Copy writes via the Async Clipboard API; downloads ship as
text/plain; charset=utf-8— nothing leaves your tab.copyclipboardtext/plainblobclient-side✓ · copiedready · done✓ Copied
shipped · ready to shipsuccess
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.
When to spell numbers
Finance, accessibility, language learning.
Cheques
Spell out the amount on a cheque. 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-correctLegal documents
Amounts often required in both digits and words. 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-cleanAccessibility
Screen-reader-friendly numeric strings. 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.
a11y-friendlyESL teaching
Show students how big numbers read aloud. 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-awareForm validation
Confirm digit + word amounts agree. 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-accurateVoice UI scripts
Pre-format numbers for TTS. 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.
losslessFrequently asked questions
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