PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

2.59 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (506 utterances, 2,317 words searched).

  1. count them . MOT · eng_USA_Brown/adam38.cha, line 1103 · Adam 3;09
  2. count them . MOT · eng_USA_Brown/adam38.cha, line 1115 · Adam 3;09
  3. count them again . MOT · eng_USA_Brown/adam38.cha, line 1509 · Adam 3;09
  4. would you like to cut them ? MOT · eng_USA_Brown/adam38.cha, line 1594 · Adam 3;09
  5. you'd like to cut them . MOT · eng_USA_Brown/adam38.cha, line 1598 · Adam 3;09
  6. what's wrong with them ? MOT · eng_USA_Brown/adam38.cha, line 1691 · Adam 3;09
  1. eng_USA_Brown/adam38.cha, line 1103 · Adam, 3;9.16
    CHIfive .
    MOTfive !
    MOT*MOT: count them .
    CHIyou have one # one # two .
    CHIdat's two .
  2. eng_USA_Brown/adam38.cha, line 1115 · Adam, 3;9.16
    CHIfive # six .
    MOTyou have how many ?
    MOT*MOT: count them .
    MOTone # two # three .
    CHIone # two # three .
  3. eng_USA_Brown/adam38.cha, line 1509 · Adam, 3;9.16
    MOThow many do you have ?
    CHIone # two # three .
    MOT*MOT: count them again .
    CHIone # two # three # four .
    MOTso how many are you missing ?
  4. eng_USA_Brown/adam38.cha, line 1594 · Adam, 3;9.16
    CHIdat's the name .
    CHII wish you could color all dese .
    MOT*MOT: would you like to cut them ?
    CHIand cut them too .
    MOTyou'd like to cut them .
  5. eng_USA_Brown/adam38.cha, line 1598 · Adam, 3;9.16
    MOTwould you like to cut them ?
    CHIand cut them too .
    MOT*MOT: you'd like to cut them .
    MOTI'll get some scissors .
    CHIMommy # but I saw them on the mantel shelf .
  6. eng_USA_Brown/adam38.cha, line 1691 · Adam, 3;9.16
    CHIscissors not right .
    MOTthey're not right ?
    MOT*MOT: what's wrong with them ?
    CHInothing .
    MOTwell # then they must be right .

Matches by age

One dot per transcript: matches per 1,000 words of everyone but CHI. Dots of the same child are joined.

Matches by child

Matches per 1,000 words, all transcripts of each child together, highest first.

  1. Adam eng_USA_Brown2.59
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/adam38.chaAdam 3;9.162,317662.59

What the pattern matched

1 different forms (lowercased). Useful to see what a pattern really catches: unexpected forms here usually mean the pattern is too broad.

  1. them6 · 100.0%