Generate adjacent-key typo

Description

Replaces one or more characters with adjacent keys.

Usage

adjacent_key_typo(word, n_typos = 1L)

Arguments

Value

Character. Word with typos

Examples

set.seed(123)
adjacent_key_typo("hello")

Analyze a gaffe comprehensively

Description

Analyze a gaffe comprehensively

Usage

analyze_gaffe(gaffe, intended)

Arguments

Value

List with comprehensive analysis

Examples

analyze_gaffe("covfefe", "coverage")

Score how well a word is a blend of two others

Description

Score how well a word is a blend of two others

Usage

blend_score(blend, word1, word2)

Arguments

Value

Numeric. Score from 0 (poor blend) to 1 (perfect blend)

Examples

blend_score("brunch", "breakfast", "lunch")

Blend two words into a portmanteau

Description

Combines the beginning of word1 with the end of word2.

Usage

blend_words(word1, word2, overlap = NULL)

Arguments

Value

Character. Blended word

Examples

blend_words("breakfast", "lunch")  # "brunch" or similar
blend_words("refute", "repudiate") # "refudiate" or similar

Phonetically Similar Consonant Pairs

Description

Pairs of consonants that are phonetically similar and commonly confused.

Usage

consonant_pairs

Format

A named list mapping consonants to their phonetically similar pairs.

Corrupt text with specified error type

Description

Corrupt text with specified error type

Usage

corrupt_text(text, type = "random", position = NULL)

Arguments

Value

Character. Corrupted text

Examples

set.seed(42)
corrupt_text("hello", type = "keyboard")
corrupt_text("coverage", type = "truncate", position = 3)

Covfefy any word.

Description

Attempt to produce your own historic typos. This function takes a word and performs the following algorithm thanks to this codegolf thread:

1. Include all characters up through the first vowel in the word. (co)

2. Identifies the next consonant after the first vowel in the word. (v)

3. Changes that consonant to a phonetically similar consonant. (f)

4. Finds the next vowel after that consonant. (e)

5. Combines the two, and repeats. (fefe)

6. Puts it all together: covfefe

Usage

covfefy(str = "coverage")

Arguments

Examples

covfefy("coverage")
covfefy("programming")
covfefy("president")
covfefy("tropical")

Covfefy any sentence.

Description

Calls covfefy() and uses rules to decide which, if any, word is covfefefied.

Usage

covfefySentence(
  sent = paste0("Despite the constant negative", " press coverage we are going ",
    "to Make America Great Again"),
  endSentence = TRUE
)

Arguments

Examples

covfefySentence(paste0("Despite the constant negative press coverage,",
                       "we are going to Make America Great Again"))

Covfefy any speech.

Description

Calls covfefySentences() and uses rules to decide which, if any, sentences are covfefefied.

Usage

covfefySpeech(
  text = system.file("extdata", "inauguration.txt", package = "covfefe"),
  out = file.path(tempdir(), "covfefe_inauguration.txt")
)

Arguments

Examples

covfefySpeech()

Detect possible source words for a blend

Description

Detect possible source words for a blend

Usage

detect_blend(blend, candidates)

Arguments

Value

Character vector. Most likely source words

Examples

detect_blend("brunch", c("breakfast", "lunch", "dinner"))

Detect likely typo type

Description

Detect likely typo type

Usage

detect_typo_type(typo, intended = NULL)

Arguments

Value

List with possible_types and confidence scores

Examples

detect_typo_type("tesy", "test")

Political Linguistics Museum Data

Description

A data frame containing 13 famous digital gaffes and typos from political figures.

Usage

gaffes

Format

A data frame with 13 rows and 8 variables:

id

Unique identifier for the gaffe

original

The intended word or phrase

gaffe

The actual typo or gaffe

person

The person who made the gaffe

year

Year the gaffe occurred

platform

Platform where the gaffe appeared (Twitter, Truth Social, etc.)

typo_type

Classification of the typo type

context

Brief description of the context

Source

Various news sources and social media archives

Garble a sentence with random corruptions

Description

Garble a sentence with random corruptions

Usage

garble_sentence(sentence, corruption_rate = 0.3)

Arguments

Value

Character. Garbled sentence

Examples

set.seed(42)
garble_sentence("This is a test", corruption_rate = 0.5)

Get phonetic group for a consonant

Description

Get phonetic group for a consonant

Usage

get_phonetic_group(consonant)

Arguments

Value

Character. Group name (labial, dental, velar, etc.)

Examples

get_phonetic_group("b")  # "labial"

Check if two keys are adjacent

Description

Check if two keys are adjacent

Usage

is_keyboard_adjacent(key1, key2)

Arguments

Value

Logical

Examples

is_keyboard_adjacent("a", "s")  # TRUE
is_keyboard_adjacent("a", "p")  # FALSE

Simulate keyboard mash (extra characters)

Description

Adds random adjacent characters to simulate accidental key presses.

Usage

keyboard_mash(word, n_extra = 3L)

Arguments

Value

Character. Word with extra characters

Examples

set.seed(456)
keyboard_mash("powerful")  # Might produce "powerfulnnz"

Filter gaffes by person

Description

Filter gaffes by person

Usage

museum_by_person(pattern)

Arguments

Value

Data frame of matching gaffes

Examples

museum_by_person("Trump")

Filter gaffes by typo type

Description

Filter gaffes by typo type

Usage

museum_by_type(type)

Arguments

Value

Data frame of matching gaffes

Examples

museum_by_type("blend")

Filter gaffes by year

Description

Filter gaffes by year

Usage

museum_by_year(year)

Arguments

Value

Data frame of matching gaffes

Examples

museum_by_year(2017)

List all gaffes in the museum

Description

List all gaffes in the museum

Usage

museum_list()

Value

Character vector of gaffe IDs

Examples

museum_list()

Look up a specific gaffe

Description

Look up a specific gaffe

Usage

museum_lookup(id)

Arguments

Value

List with gaffe details

Examples

museum_lookup("covfefe")

Get a random gaffe from the museum

Description

Get a random gaffe from the museum

Usage

museum_random()

Value

List with gaffe details

Examples

set.seed(42)
museum_random()

Parse syllable into onset, nucleus, coda

Description

Parse syllable into onset, nucleus, coda

Usage

onset_nucleus_coda(syllable)

Arguments

Value

List with onset, nucleus, coda components

Examples

onset_nucleus_coda("cat")  # list(onset="c", nucleus="a", coda="t")

Calculate phonetic distance between words

Description

Uses Soundex codes to measure phonetic similarity.

Usage

phonetic_distance(word1, word2)

Arguments

Value

Numeric. Distance (0 = identical, higher = more different)

Examples

phonetic_distance("coverage", "covfefe")

Phonetic Consonant Groups

Description

Consonants grouped by place of articulation.

Usage

phonetic_groups

Format

A named list with groups: labial, dental, velar, sibilant, liquid, glide.

Shift consonant to phonetically similar consonant

Description

Shift consonant to phonetically similar consonant

Usage

phonetic_shift(word, target)

Arguments

Value

Character. Transformed word

Examples

phonetic_shift("coverage", "v")  # "coferage"

QWERTY Keyboard Adjacency Data

Description

A list containing adjacent keys for each letter on a QWERTY keyboard.

Usage

qwerty_adjacency

Format

A named list with 26 elements (a-z), each containing a character vector of adjacent key letters.

Get adjacent keys on QWERTY keyboard

Description

Get adjacent keys on QWERTY keyboard

Usage

qwerty_adjacent(key)

Arguments

Value

Character vector of adjacent keys

Examples

qwerty_adjacent("f")

Calculate QWERTY distance between two keys

Description

Uses Euclidean distance based on key positions.

Usage

qwerty_distance(key1, key2)

Arguments

Value

Numeric distance

Examples

qwerty_distance("a", "s")  # Adjacent = 1
qwerty_distance("a", "p")  # Far apart

QWERTY Keyboard Layout Data

Description

A list containing row and column positions for each letter on a QWERTY keyboard.

Usage

qwerty_layout

Format

A named list with 26 elements (a-z), each containing a named numeric vector with 'row' and 'col' positions.

Calculate Soundex code

Description

American Soundex algorithm for phonetic encoding.

Usage

soundex(word)

Arguments

Value

Character. 4-character Soundex code

Examples

soundex("Robert")     # "R163"
soundex("Rupert")     # "R163" (same as Robert)
soundex("Washington") # "W252"

Soundex Encoding Map

Description

Mapping of consonants to their Soundex digit codes.

Usage

soundex_map

Format

A named character vector mapping consonants to digits 1-6.

Suggest corrections for a typo

Description

Suggest corrections for a typo

Usage

suggest_corrections(typo, dictionary = NULL)

Arguments

Value

Character vector of suggested corrections

Examples

suggest_corrections("tesy")

Split word into syllables

Description

Uses a simplified vowel-based algorithm.

Usage

syllabify(word)

Arguments

Value

Character vector of syllables

Examples

syllabify("hello")     # c("hel", "lo")
syllabify("coverage")  # c("cov", "er", "age")

Count syllables in a word

Description

Count syllables in a word

Usage

syllable_count(word)

Arguments

Value

Integer. Number of syllables

Examples

syllable_count("hello")  # 2

Swap syllables between two words

Description

Swap syllables between two words

Usage

syllable_swap(word1, word2, position = 1L)

Arguments

Value

Character vector of length 2 with swapped words

Examples

syllable_swap("coverage", "president", 1)

Shift vowels in a word

Description

Shift vowels in a word

Usage

vowel_shift(word, from, to)

Arguments

Value

Character. Transformed word

Examples

vowel_shift("test", "e", "i")  # "tist"

Vowel Shift Mappings

Description

Possible vowel shifts inspired by historical sound changes.

Usage

vowel_shifts

Format

A named list mapping vowels to possible shift targets.