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Text Counting & Analysis Tools

Reading Time Calculator

Calculate reading time from pasted text or a direct word count, compare silent-reading and speaking durations, and reverse-solve how many words fit a target number of minutes at your chosen WPM.

Text or word-count inputRead + speak timeTarget time → words8-speed pace matrix
Reading-time planning authority

Words → time, then reverse the equation

Use text when you have the draft, direct word count when you already know the length, or a target duration when you need a word budget. The same WPM assumptions stay visible in every direction.

Browser-local timing math
—words
—silent reading
—speaking aloud
—page equivalents
Target-duration reverse solve
—words that fit at reading WPM
—page equivalents
—
Ready.
0Segmented words
0 secEstimated reading time at the selected rate

Counts run locally in your browser. When available, word, sentence, and grapheme segmentation uses the browser’s Unicode-aware Intl.Segmenter; fallback rules are used on older browsers.

Read + speak time & content stats

Keep the adjustable reading-speed calculator and add speaking time, structural counts, pace presets and a reusable “min read” label.

Read + speak

Publishable label

0 min read

Text structure

0 sentences · 0 paragraphs

238 WPM is a practical non-fiction default, not a promise for every reader or content type.

Independent text evidence audit

Recount the current text with a separate browser-local evidence layer. It reads the existing tool input; it does not replace the primary counter or send text anywhere.

Enter text in the tool above, then refresh this audit.
Text evidence audit ready.

Core counting & writing metrics

Start with the broad counter that matches the question, then move to focused frequency, reading-time or syllable analysis. Specialist readability, repetition and writing-goal tools remain available from the full hub.

All 28 text analysis tools

Text analysis with explicit counting semantics

The result distinguishes Unicode graphemes, code points, word/sentence boundaries, line endings or normalization where those details change the meaning of the count. Browser-local analysis stays live without treating approximate language heuristics as exact facts.

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