PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

4.39 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (400 utterances, 1,595 words searched).

  1. that's right ! MOT · bilingual_eng_Genesee/oli23b04m.cha, line 372 · Olivier 2;03
  2. that's right . MOT · bilingual_eng_Genesee/oli23b04m.cha, line 453 · Olivier 2;03
  3. that's right . MOT · bilingual_eng_Genesee/oli23b04m.cha, line 605 · Olivier 2;03
  4. we [/] we [/] we won't go right away . MOT · bilingual_eng_Genesee/oli23b04m.cha, line 938 · Olivier 2;03
  5. that's right, sweetie . MOT · bilingual_eng_Genesee/oli23b04m.cha, line 1070 · Olivier 2;03
  6. that's right . MOT · bilingual_eng_Genesee/oli23b04m.cha, line 1146 · Olivier 2;03
  7. that's right . MOT · bilingual_eng_Genesee/oli23b04m.cha, line 1293 · Olivier 2;03
  1. bilingual_eng_Genesee/oli23b04m.cha, line 372 · Olivier, 2;3.20
    MOTokay .
    CHI0.
    MOT*MOT: that's right !
    MOTthat's a good boy .
    CHI0.
  2. bilingual_eng_Genesee/oli23b04m.cha, line 453 · Olivier, 2;3.20
    CHI+, train .
    MOTa choochoo train .
    MOT*MOT: that's right .
    CHIoù elle est la gros auto ?
    MOT0.
  3. bilingual_eng_Genesee/oli23b04m.cha, line 605 · Olivier, 2;3.20
    MOTnow what's that ?
    CHI0.
    MOT*MOT: that's right .
    MOTwhy does it go there ?
    MOTwhy do you put it there ?
  4. bilingual_eng_Genesee/oli23b04m.cha, line 938 · Olivier, 2;3.20
    MOTwe'll go later .
    MOTkay [: okay] ?
    MOT*MOT: we [/] we [/] we won't go right away .
    MOTlater .
    CHIlà le gros auto ?
  5. bilingual_eng_Genesee/oli23b04m.cha, line 1070 · Olivier, 2;3.20
    MOTall around the world .
    OBSoh !
    MOT*MOT: that's right, sweetie .
    CHI0.
    MOTall around the world .
  6. bilingual_eng_Genesee/oli23b04m.cha, line 1146 · Olivier, 2;3.20
    MOTMami +...
    CHIMami Marie .
    MOT*MOT: that's right .
    MOTMami Marie .
    OBS0.
  7. bilingual_eng_Genesee/oli23b04m.cha, line 1293 · Olivier, 2;3.20
    MOTwhat did +/.
    CHIxxx McDonald's .
    MOT*MOT: that's right .
    MOTwe went to McDonald's .
    MOTand what did you eat at McDonald's ?

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. Olivier bilingual_eng_Genesee4.39
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
bilingual_eng_Genesee/oli23b04m.chaOlivier 2;3.201,595774.39

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. right7 · 100.0%