package readability_metrics

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Classic English readability metrics with no dependencies

Install 

dune-project
 Dependency

belikenative.com Readme Changelog Edit opam file Versions (1)

Authors

  1. M
    Michal Lip <51033404+theluckystrike@users.noreply.github.com>

Maintainers

  1. M
    Michal Lip <51033404+theluckystrike@users.noreply.github.com>

Sources

readability_metrics-0.1.0.tar.gz
sha256=81d315a2b3b1530a6c413c1276efeb9479b0096762b00322ec55a637d069cb45
sha512=c3a8021ed995571143f417145bd7fa4149ab8466763d22c3f7ed14470941552f173b703f3cf78887b2ac134d3f74d672c550b9aceb3b98fa329428136b7f79f2

doc/readability_metrics/Readability_metrics/index.html

Module Readability_metricsSource

Classic English readability metrics, with no dependencies outside the OCaml standard library.

The library is deliberately split into three layers:

  • tokenisation (words, sentences, syllables_in_word) — plain functions you can call on their own and test in isolation;
  • counting (stats) — a single pass that produces the six counts every published readability formula is built from;
  • formulas (flesch_reading_ease and friends) — each exposed twice, once taking a string and once taking a stats record, so that a caller computing several scores over the same text pays for the counting once.

Accuracy caveats

Every formula below is defined over counts of sentences, words, syllables and letters. Those counts come from heuristics, not from a parser or a pronunciation dictionary, so scores are approximations. In particular:

  • sentence splitting is punctuation based and does not know about abbreviations, so "Dr. Who" counts as two sentences;
  • syllable counting is a vowel-group heuristic tuned for English and will be wrong on loanwords, names and initialisms. Its systematic error is vowel hiatus, where two adjacent vowels belong to different syllables: "science", "create" and "idea" each come out one syllable short. Over a document this shows up as a small downward bias in the syllable count, and therefore a slightly optimistic Flesch score.

These are the same limitations the widely used Python textstat and JavaScript text-readability packages have; the formulas themselves are reproduced exactly as published.

Tokenisation

Sourceval words : string -> string list

words text splits text into word tokens. A token is a maximal run of ASCII letters, optionally containing internal apostrophes or hyphens ("don't" and "well-known" are one token each). Digits and punctuation are not words. Returns tokens in order of appearance.

Sourceval sentences : string -> string list

sentences text splits text on the sentence-final punctuation ., !, ? and on newline-separated blocks, then drops any fragment that contains no word. Consecutive terminators ("...", "?!") count as one boundary. A trailing fragment without a terminator still counts as a sentence, so "hello" is one sentence.

Sourceval syllables_in_word : string -> int

syllables_in_word w estimates the number of English syllables in the single token w, using a vowel-group heuristic:

  • letters are lowercased and non-letters dropped;
  • maximal runs of aeiouy each contribute one syllable;
  • a silent trailing "e" is removed, unless the word ends in a consonant followed by "le" ("table", "little"), and unless removing it would leave no vowel group at all;
  • the trailing inflections "es" and "ed" do not add a syllable when the preceding letter is not a sibilant or t/d ("walked" is one syllable, "wanted" is two);
  • the result is never less than 1 for a non-empty token.

syllables_in_word "" is 0.

Counting

Sourcetype stats = {
  1. characters : int;
    (*

    Letters only. Spaces, digits and punctuation are excluded, which is the convention the Coleman-Liau index and the ARI were calibrated against.

    *)
  2. words : int;
    (*

    Number of tokens returned by words.

    *)
  3. sentences : int;
    (*

    Number of fragments returned by sentences.

    *)
  4. syllables : int;
    (*

    Sum of syllables_in_word over all words.

    *)
  5. polysyllables : int;
    (*

    Words of three syllables or more.

    *)
  6. complex_words : int;
    (*

    Gunning fog "complex" words: three syllables or more, excluding words made polysyllabic only by an "es" or "ed" inflection. Always at most polysyllables.

    *)
  7. long_words : int;
    (*

    Words of more than six letters (the LIX definition).

    *)
  8. very_long_words : int;
    (*

    Words of seven letters or more (the RIX definition).

    *)
}

The counts every formula in this module is a function of.

Sourceval stats : string -> stats

stats text tokenises text once and returns all counts. On text with no words every field is 0.

Sourceval empty_stats : stats

All fields 0. Useful as a fold seed.

Formulas

Each formula is given for a stats record (*_of_stats) and, for convenience, directly for a string. The string version is exactly f_of_stats (stats text).

All of them return nan when the text has no words or no sentences, since every formula divides by at least one of those counts. Use Float.is_nan to detect it rather than testing for a sentinel.

Sourceval flesch_reading_ease : string -> float
Sourceval flesch_reading_ease_of_stats : stats -> float

Flesch reading ease, Flesch (1948): 206.835 - 1.015 * (words / sentences) - 84.6 * (syllables / words). Higher is easier; 60-70 is "plain English", above 90 is very easy. The scale is open ended and can go negative or above 100.

Sourceval flesch_kincaid_grade : string -> float
Sourceval flesch_kincaid_grade_of_stats : stats -> float

Flesch-Kincaid grade level, Kincaid et al. (1975): 0.39 * (words / sentences) + 11.8 * (syllables / words) - 15.59. The result is a US school grade.

Sourceval gunning_fog : string -> float
Sourceval gunning_fog_of_stats : stats -> float

Gunning fog index, Gunning (1952): 0.4 * ((words / sentences) + 100 * (complex_words / words)).

Sourceval smog : string -> float
Sourceval smog_of_stats : stats -> float

SMOG grade, McLaughlin (1969): 1.043 * sqrt (polysyllables * 30 / sentences) + 3.1291. McLaughlin specified a 30-sentence sample; the formula extrapolates from shorter text but is unreliable below roughly 10 sentences.

Sourceval coleman_liau : string -> float
Sourceval coleman_liau_of_stats : stats -> float

Coleman-Liau index, Coleman and Liau (1975): 0.0588 * l - 0.296 * s - 15.8, where l is letters per 100 words and s is sentences per 100 words. Unlike the Flesch family this one needs no syllable counting, so it is the most robust of the set.

Sourceval automated_readability_index : string -> float
Sourceval automated_readability_index_of_stats : stats -> float

Automated readability index, Senter and Smith (1967): 4.71 * (characters / words) + 0.5 * (words / sentences) - 21.43.

Sourceval lix : string -> float
Sourceval lix_of_stats : stats -> float

Läsbarhetsindex, Björnsson (1968): (words / sentences) + 100 * (long_words / words). Below 30 is very easy, above 60 is very hard. Language independent by design.

Sourceval rix : string -> float
Sourceval rix_of_stats : stats -> float

Anderson's RIX (1983): very_long_words / sentences.

Reports

Sourcetype report = {
  1. text_stats : stats;
  2. flesch_reading_ease_score : float;
  3. flesch_kincaid_grade_score : float;
  4. gunning_fog_score : float;
  5. smog_score : float;
  6. coleman_liau_score : float;
  7. ari_score : float;
  8. lix_score : float;
  9. rix_score : float;
  10. consensus_grade : float;
    (*

    Median of the five US-grade-scale formulas (Flesch-Kincaid, fog, SMOG, Coleman-Liau, ARI). nan if the stats are empty.

    *)
}
Sourceval report : string -> report

report text computes the stats once and every score from them.

Sourceval report_of_stats : stats -> report
Sourceval pp_report : Format.formatter -> report -> unit

Human readable multi-line rendering, one metric per line.

Sourceval report_to_json : report -> string

A single-line JSON object. Only ASCII, no dependencies; nan is rendered as JSON null.