Count chars, words, lines, paragraphs and reading time.
Updated
with spaces
0 B
Adult silent reading · 238 wpm
Presentation pace · 130 wpm
Add text to see keyword density.
Tip: counts use Intl.Segmenter where available, so emoji and CJK characters are counted as users perceive them.
Quick start
Paste your text — every metric updates live, with zero data leaving your browser.
Drop draft copy, an article, a tweet, or any other text into the editor. Counts appear instantly.
Words, characters, sentences, paragraphs, lines and bytes are all displayed alongside reading and speaking time estimates.
Scan the top-10 keyword table to spot accidental repetition or confirm your target terms appear at a sensible rate.
In-depth guide
This counter gives you the basic measurements every writer needs — words, characters, sentences, paragraphs, lines — plus reading time, speaking time and keyword density, all updating live as you type. Everything runs locally in your browser, so the draft of your novel never leaves your machine.
., !, ? followed by whitespace.Reading time uses 238 words per minute — the average adult silent-reading speed from a 2019 meta-analysis of 190 studies (Brysbaert, Journal of Memory and Language). Speed varies with difficulty: simple narrative averages ~260 wpm, technical prose ~180 wpm.
Speaking time uses 130 words per minute — a comfortable presentation pace that allows for pauses and emphasis. Conversational speech is faster (~150 wpm); auctioneers hit 300+.
Want to find a specific phrase instead? Use your browser's Find (⌘/Ctrl+F) — it's faster than any external tool.
Density = occurrences ÷ total words. The table here shows the top 10 lower-cased tokens, punctuation stripped. It's useful for:
What it isn't useful for: gaming search engines. Modern ranking factors care about topical completeness, entity coverage and user signals — not keyword count.
No. Counting runs entirely in your browser using JavaScript and the Intl.Segmenter API. You can verify in DevTools → Network: zero requests fire while you type.
When the browser supports Intl.Segmenter, we use locale-aware word segmentation, which correctly handles non-Latin scripts (Chinese, Japanese, Thai). On older browsers we fall back to splitting on whitespace.
We use grapheme-cluster counting, so a family emoji like 👨👩👧 is one character — the same as how you perceive it. JavaScript's `.length` would report 11 because it counts UTF-16 code units, which isn't what most users want.
Reading time = words ÷ 238 wpm. That's the average adult silent-reading speed from a 2019 meta-analysis published in the Journal of Memory and Language. Speaking time uses 130 wpm, which is a comfortable presentation pace.
We split on `.`, `!` or `?` followed by whitespace or end-of-text. This works reliably for most prose; it can miscount in technical text full of abbreviations like 'e.g.' or 'Mr.' — treat the figure as approximate.
It's how often a word appears divided by the total number of words. SEO advice used to obsess over keeping target keywords at 1-3%; modern search engines don't reward that, but the metric still helps you spot accidental repetition.
Characters are UTF-8 encoded for transmission. ASCII characters are 1 byte; accented Latin letters 2 bytes; CJK ideographs 3 bytes; most emoji 4 bytes. Tweet limits, database column sizes and API payload caps are typically in bytes, not characters.
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