PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

3.42 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (534 utterances, 2,049 words searched).

  1. would you like a biscuit ? MOT · eng_british_Manchester_II/nic05b.cha, line 268 · Nicole 2;02
  2. what would panda like to eat ? MOT · eng_british_Manchester_II/nic05b.cha, line 863 · Nicole 2;02
  3. panda would like # an egg . MOT · eng_british_Manchester_II/nic05b.cha, line 865 · Nicole 2;02
  4. do you think dolly would like a burger ? MOT · eng_british_Manchester_II/nic05b.cha, line 922 · Nicole 2;02
  5. maybe Co_co would like some burger . MOT · eng_british_Manchester_II/nic05b.cha, line 970 · Nicole 2;02
  6. would Nicole like one ? MOT · eng_british_Manchester_II/nic05b.cha, line 1208 · Nicole 2;02
  7. would you like to sing Rachel a song ? MOT · eng_british_Manchester_II/nic05b.cha, line 1458 · Nicole 2;02
  1. CHIbickie .
    CHIbickie .
    MOT*MOT: would you like a biscuit ?
    CHIyeah .
    CHIxxx .
  2. MOTthere , fully clothed now .
    MOTwhat else is in there ?
    MOT*MOT: what would panda like to eat ?
    MOTpanda would like # an egg .
    MOTcan you find me an egg ?
  3. MOTwhat else is in there ?
    MOTwhat would panda like to eat ?
    MOT*MOT: panda would like # an egg .
    MOTcan you find me an egg ?
    CHIyeah .
  4. MOTshall we make a burger ?
    MOTshall we make a burger up for dolly ?
    MOT*MOT: do you think dolly would like a burger ?
    MOTthere .
    MOTgot a bun .
  5. MOTare you going to put the cheese on top of the meat for Mummy ?
    MOTthen you can feed it to dolly , can't you ?
    MOT*MOT: maybe Co_co would like some burger .
    MOTdo you think ?
    CHIno .
  6. MOThuh ?
    CHINicole .
    MOT*MOT: would Nicole like one ?
    CHIyeah .
    MOTyou've just said no , you don't like it .
  7. MOTno Nicole get off me please .
    MOTare you singing ?
    MOT*MOT: would you like to sing Rachel a song ?
    CHIyeah .
    MOTare you going to put the food away in the basket ?

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. Nicole eng_british_Manchester_II3.42
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/nic05b.chaNicole 2;2.052,049773.42

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. would7 · 100.0%