MLU Calculator

Mean Length of Utterance in morphemes and words, plus the matching Brown's stage. Paste the transcript — the calculator handles the rest. Data never leaves your browser.

MLU-morphemesBrown's StagesClient-Side

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One utterance per line. The calculator segments, counts, and scores the sample instantly in your browser.

Paste a transcript above to compute MLU-morphemes, MLU-words, and the matching Brown's stage.

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  • Computing MLU-morphemes and MLU-words from a transcribed language sample
  • Assigning a preschool child to a Brown stage based on expressive language
  • Tracking progress across sessions for a child on your caseload
  • Preparing a quick summary metric for an evaluation report
  • Teaching graduate SLP students how MLU is calculated

Don't use for

  • Analysing samples shorter than 50 utterances — MLU is unstable below that threshold
  • Assessing bilingual children on an English-only sample (use dual-language LSA instead)
  • Diagnosing language disorder from MLU alone — combine with lexical diversity, PGU, and narrative measures
  • Scoring SALT-coded transcripts with detailed morpheme annotations — use SALT or CLAN for those

What is MLU?

Mean Length of Utterance (MLU) is the average number of morphemes (or words) per utterance in a child's spontaneous language sample. Introduced by Roger Brown in 1973, it is the most widely reported index of expressive language in speech-language pathology and the entry point for Brown's stages of grammatical development.

MLU grows predictably with age and grammatical maturity. A child at MLU 1.5 is combining two words; a child at MLU 4.0 is producing coordinated sentences with articles and regular past tense. Because MLU tracks grammar better than raw age, clinicians use it to decide whether a child's expressive language is developing on schedule or falling behind peers.
How to compute MLU. Transcribe 50 to 100 utterances from a free-play or narrative sample. Segment the transcript into C-units or communication units (one independent clause plus any attached subordinate clauses). Count morphemes using Brown's rules, sum across all utterances, and divide by the number of utterances.

Brown's Stages and MLU Ranges

Brown (1973) partitioned early language development into five stages based on MLU ranges. Each stage corresponds to the emergence of specific grammatical structures:

  • Stage I (MLU 1.0 - 1.99, ~12-26 mo): Single words and two-word combinations.
  • Stage II (MLU 2.0 - 2.49, ~27-30 mo): Present progressive -ing, prepositions in and on, plural -s.
  • Stage III (MLU 2.5 - 2.99, ~31-34 mo): Yes/no questions, wh-questions, negation, irregular past, possessive -s.
  • Stage IV (MLU 3.0 - 3.74, ~35-40 mo): Embedded sentences, articles, regular past -ed, third person singular -s.
  • Stage V (MLU 3.75 - 4.49, ~41-46 mo): Coordinated sentences, contractible copula and auxiliary.
  • Stage V+ (MLU >= 4.5, 47+ mo): Adult-like syntax, mastery of Brown's 14 morphemes.

A child whose MLU falls 1 SD below the age-matched mean on Rice et al. (2010) or SUGAR (Pavelko & Owens 2017) norms warrants closer assessment. Do not treat MLU as a pass/fail indicator on its own — combine it with lexical diversity, grammaticality (PGU), and narrative measures for a fuller picture.

How This Calculator Works

Paste your language sample into the textarea, one utterance per line. The calculator:

  • Splits the sample into utterances (newlines first, sentence-ending punctuation as a fallback).
  • Counts words per utterance by whitespace-tokenising and skipping punctuation-only tokens.
  • Counts morphemes per utterance using Brown's rules: contractions = 2, regular -s/-ed/-ing = 2, irregular past/plural = 1, catenatives and diminutives = 1, compound words (hyphenated) = 1.
  • Reports MLU-morphemes, MLU-words, total utterances, and total morphemes, and maps the MLU-morphemes score to the closest Brown's stage.

The morpheme counter is heuristic. For research-grade coding, verify contested tokens by hand. For most clinical screening use cases, the calculator matches the worked examples in the Brown corpus literature closely enough to support reporting.

Frequently Asked Questions