Type‑Token Ratio plus MATTR moving average — see how much your vocabulary repeats.
Use TTR and MATTR to evaluate vocabulary range — common in language-learning assessments, child-language research, and stylometry. MATTR is preferable for comparing documents of different lengths because raw TTR drops as text grows.
TTR and MATTR are complementary: TTR is intuitive but length-sensitive; MATTR is length-invariant but harder to explain. For formal research, prefer MATTR or one of its cousins (MTLD, HD-D).
Type-token ratio (TTR) is the simplest measure of vocabulary variety: unique words / total words.
Because TTR drops as text gets longer, this tool also computes the Moving Average Type-Token Ratio (MATTR) over a 50-word window, which is length-invariant.
You also get a list of "hapax legomena" — words that appear exactly once.
The ratio of unique words to total words. TTR drops as text gets longer, so it's sensitive to length.
Moving Average Type-Token Ratio. It computes TTR over a sliding window (we use 50 words) so the score is comparable across documents of different lengths.
Common words like 'the' and 'and' repeat constantly, so the ratio of unique words to total words falls steadily as the text grows. This length sensitivity is the main reason MATTR is preferred for comparing texts of different sizes.
There is no universal threshold because TTR depends heavily on text length, but within similar-length samples a higher ratio signals richer vocabulary. For fair comparisons use MATTR, which holds the window size constant.
Input
The dog ran. The dog jumped. The dog barked. The dog slept.
Output
TTR: 0.45 (5 unique / 11 total) — Low diversity.
"The" and "dog" repeat heavily; only "ran", "jumped", "barked", and "slept" add new types. Low TTR is typical of beginner writing or restricted-vocabulary text.
% content words vs. function words.
analysisTotal + per‑word syllable counts.
analysisHighlight passive sentences in your writing.
analysisSentence length stats and variety score.