PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

2.99 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (547 utterances, 2,679 words searched).

  1. hello # Joe . MOT · eng_USA_Brown/adam43.cha, line 2736 · Adam 4;01
  2. well # you have to say hello # Joe then . MOT · eng_USA_Brown/adam43.cha, line 2751 · Adam 4;01
  3. if I'm Peter # you're Joe . MOT · eng_USA_Brown/adam43.cha, line 2754 · Adam 4;01
  4. well then I'll say hello Joe and you say hello +... MOT · eng_USA_Brown/adam43.cha, line 2762 · Adam 4;01
  5. hello # Joe . MOT · eng_USA_Brown/adam43.cha, line 2773 · Adam 4;01
  6. hello # Joe . MOT · eng_USA_Brown/adam43.cha, line 2798 · Adam 4;01
  7. it would be a lot easier if you were both named Joe . URS · eng_USA_Brown/adam43.cha, line 2949 · Adam 4;01
  8. hello # Joe . MOT · eng_USA_Brown/adam43.cha, line 2961 · Adam 4;01
  1. MOTwell # then you have to say hello # Peter .
    CHIhello # Peter .
    MOT*MOT: hello # Joe .
    MOThow're you ?
    CHIfine .
  2. MOThello # Peter .
    CHIno # you Peter .
    MOT*MOT: well # you have to say hello # Joe then .
    MOTif I'm Peter # you're Joe .
    MOTis that right ?
  3. CHIno # you Peter .
    MOTwell # you have to say hello # Joe then .
    MOT*MOT: if I'm Peter # you're Joe .
    MOTis that right ?
    CHIyes .
  4. MOTis that right ?
    CHIyes .
    MOT*MOT: well then I'll say hello Joe and you say hello +...
    CHI+, Peter .
    MOTPeter .
  5. MOTthat's right .
    CHIhello # Peter .
    MOT*MOT: hello # Joe .
    MOTwhere're you going ?
    CHIto camp .
  6. MOTyes # I did .
    CHIhi # Peter .
    MOT*MOT: hello # Joe .
    MOTnice day # isn't it ?
    CHIbut it's tomorrow # huh ?
  7. MOThmm ?
    CHIpush dis # Peter .
    URS*URS: it would be a lot easier if you were both named Joe .
    CHIhey # Joe .
    CHIJoe # let's take +...
  8. MOTthis is the first time he's tried this naming .
    CHIhi # Peter .
    MOT*MOT: hello # Joe .
    MOTwe're at the farm now .
    CHIlet's park our car .

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_Brown2.99
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/adam43.chaAdam 4;1.152,679882.99

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. joe8 · 100.0%