PHPCLANCHILDES with regular expressions

5 matches in 5 utterances

3.79 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (366 utterances, 1,319 words searched).

  1. what would you do then ? FAT · eng_USA_Brown/sarah087.cha, line 100 · Sarah 4;00
  2. then he gets up (a)n(d) has a peanut+butter sandwich . MOT · eng_USA_Brown/sarah087.cha, line 700 · Sarah 4;00
  3. (a)n(d) then she got drowsy . MOT · eng_USA_Brown/sarah087.cha, line 1109 · Sarah 4;00
  4. (a)n(d) then she says . MOT · eng_USA_Brown/sarah087.cha, line 1148 · Sarah 4;00
  5. (a)n(d) then she gets . MOT · eng_USA_Brown/sarah087.cha, line 1150 · Sarah 4;00
  1. eng_USA_Brown/sarah087.cha, line 100 · Sarah, 4;0.05
    FATmight come off .
    CHII +/.
    FAT*FAT: what would you do then ?
    CHII'd xxx put it back on .
    CHI<going # going> [/] # going .
  2. eng_USA_Brown/sarah087.cha, line 700 · Sarah, 4;0.05
    MOTmy husband eats peanut+butter (un)till it comes out his ears .
    MOTyou give him a great big man meal # he'll sit down (a)n(d) eat it .
    MOT*MOT: then he gets up (a)n(d) has a peanut+butter sandwich .
    MOTno matter how much he eats # he has that peanut+butter sandwich afterwards .
    CHII have a peanut+butter sandwich .
  3. eng_USA_Brown/sarah087.cha, line 1109 · Sarah, 4;0.05
    CHIMommy .
    MOTxxx .
    MOT*MOT: (a)n(d) then she got drowsy .
    MOTwhat is it .
    MOTwhat does Drowsy say ?
  4. eng_USA_Brown/sarah087.cha, line 1148 · Sarah, 4;0.05
    MOT+" I want a drink of water .
    CHIum .
    MOT*MOT: (a)n(d) then she says .
    MOT(a)n(d) then she gets .
    CHInight+night close your eyes .
  5. eng_USA_Brown/sarah087.cha, line 1150 · Sarah, 4;0.05
    CHIum .
    MOT(a)n(d) then she says .
    MOT*MOT: (a)n(d) then she gets .
    CHInight+night close your eyes .
    MOTnight+night # close your eyes ?

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. Sarah eng_USA_Brown3.79
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah087.chaSarah 4;0.051,319553.79

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. then5 · 100.0%