PHPCLANCHILDES with regular expressions

9 matches in 9 utterances

6.36 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (356 utterances, 1,416 words searched).

  1. here you are . MOT · eng_british_Manchester_II/liz15b.cha, line 21 · Liz 2;04
  2. come here then . MOT · eng_british_Manchester_II/liz15b.cha, line 332 · Liz 2;04
  3. come here then . MOT · eng_british_Manchester_II/liz15b.cha, line 342 · Liz 2;04
  4. here's your ribbon dolly . MOT · eng_british_Manchester_II/liz15b.cha, line 423 · Liz 2;04
  5. I'm making a truck here . MOT · eng_british_Manchester_II/liz15b.cha, line 963 · Liz 2;04
  6. oh here it is . MOT · eng_british_Manchester_II/liz15b.cha, line 1328 · Liz 2;04
  7. come here . MOT · eng_british_Manchester_II/liz15b.cha, line 1590 · Liz 2;04
  8. come here . MOT · eng_british_Manchester_II/liz15b.cha, line 1592 · Liz 2;04
  9. come here . MOT · eng_british_Manchester_II/liz15b.cha, line 1594 · Liz 2;04
  1. CHIpanda .
    MOTpanda panda .
    MOT*MOT: here you are .
    MOTput his feet in first .
    MOTthere we go .
  2. CHIyeah .
    MOTyeah ?
    MOT*MOT: come here then .
    CHIin me .
    CHIthis one .
  3. MOTyes in you .
    CHIno .
    MOT*MOT: come here then .
    MOTno ?
    CHIput dolly .
  4. MOTthere we go .
    CHII want these pants on .
    MOT*MOT: here's your ribbon dolly .
    MOTis she going to have those pants on , is she ?
    CHIyeah .
  5. MOTbecause they're fun to play with .
    MOTI like playing with them .
    MOT*MOT: I'm making a truck here .
    CHIwhy ?
    MOTjust thought it'd be good .
  6. CHIwhere 0is [*] the lid ?
    MOTer I [/] I don't know .
    MOT*MOT: oh here it is .
    MOTthere you go .
    CHIthere .
  7. CHII don't need these clothes .
    CHII want these off .
    MOT*MOT: come here .
    MOTcome here .
    MOTcome here .
  8. CHII want these off .
    MOTcome here .
    MOT*MOT: come here .
    MOTcome here .
    MOTlet's have a huggle@c eh ?
  9. MOTcome here .
    MOTcome here .
    MOT*MOT: come here .
    MOTlet's have a huggle@c eh ?
    MOTyeah that's nice .

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. Liz eng_british_Manchester_II6.36
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/liz15b.chaLiz 2;4.031,416996.36

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. here9 · 100.0%