PHPCLANCHILDES with regular expressions

10 matches in 10 utterances

6.22 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (364 utterances, 1,609 words searched).

  1. let's have a xxx with panda # all right . MOT · bilingual_eng_Deuchar/861023eg.cha, line 286 · M 1;03
  2. panda [>] . MOT · bilingual_eng_Deuchar/861023eg.cha, line 507 · M 1;03
  3. is it panda M ? GRA · bilingual_eng_Deuchar/861023eg.cha, line 512 · M 1;03
  4. there you're sitting in panda # and +... GRA · bilingual_eng_Deuchar/861023eg.cha, line 517 · M 1;03
  5. baby panda . MOT · bilingual_eng_Deuchar/861023eg.cha, line 518 · M 1;03
  6. panda . GRA · bilingual_eng_Deuchar/861023eg.cha, line 522 · M 1;03
  7. pan [<] panda . GRA · bilingual_eng_Deuchar/861023eg.cha, line 719 · M 1;03
  8. panda isn't it ? MOT · bilingual_eng_Deuchar/861023eg.cha, line 728 · M 1;03
  9. can I see panda ? GRA · bilingual_eng_Deuchar/861023eg.cha, line 729 · M 1;03
  10. like this panda isn't it ? GRA · bilingual_eng_Deuchar/861023eg.cha, line 740 · M 1;03
  1. bilingual_eng_Deuchar/861023eg.cha, line 286 · M, 1;3.29
    MOTnever mind .
    GRAgranny's bony knee xxx .
    MOT*MOT: let's have a xxx with panda # all right .
    MOTxxx this is a funny shape isn't it ?
    MOTwhat is this ?
  2. bilingual_eng_Deuchar/861023eg.cha, line 507 · M, 1;3.29
    MOTyou changed his <name have you> [>] ?
    GRAwhat is it [<] ?
    MOT*MOT: panda [>] .
    CHIyyy [<] .
    GRAis it panda M ?
  3. bilingual_eng_Deuchar/861023eg.cha, line 512 · M, 1;3.29
    MOTpanda [>] .
    CHIyyy [<] .
    GRA*GRA: is it panda M ?
    GRAthat's right she'd like to sit +...
    MOTooh !
  4. bilingual_eng_Deuchar/861023eg.cha, line 517 · M, 1;3.29
    MOTooh !
    MOTthere we are .
    GRA*GRA: there you're sitting in panda # and +...
    MOTbaby panda .
    GRAone of those photos that go on and on and on .
  5. bilingual_eng_Deuchar/861023eg.cha, line 518 · M, 1;3.29
    MOTthere we are .
    GRAthere you're sitting in panda # and +...
    MOT*MOT: baby panda .
    GRAone of those photos that go on and on and on .
    MOTyes .
  6. bilingual_eng_Deuchar/861023eg.cha, line 522 · M, 1;3.29
    GRAone of those photos that go on and on and on .
    MOTyes .
    GRA*GRA: panda .
    CHI0.
    CHIyyy .
  7. bilingual_eng_Deuchar/861023eg.cha, line 719 · M, 1;3.29
    CHIyyy .
    MOTwhat's that [>] ?
    GRA*GRA: pan [<] panda .
    MOTwhat's that ?
    CHIpa .
  8. bilingual_eng_Deuchar/861023eg.cha, line 728 · M, 1;3.29
    CHImmhmm .
    CHIyyy .
    MOT*MOT: panda isn't it ?
    GRAcan I see panda ?
    CHIyyy .
  9. bilingual_eng_Deuchar/861023eg.cha, line 729 · M, 1;3.29
    CHIyyy .
    MOTpanda isn't it ?
    GRA*GRA: can I see panda ?
    CHIyyy .
    MOTthank you .
  10. bilingual_eng_Deuchar/861023eg.cha, line 740 · M, 1;3.29
    MOTgive it to Granny ?
    GRAcan I see pandas again ?
    GRA*GRA: like this panda isn't it ?
    GRAoh !
    MOTbigger than you .

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. M bilingual_eng_Deuchar6.22
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
bilingual_eng_Deuchar/861023eg.chaM 1;3.291,60910106.22

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. panda10 · 100.0%