PHPCLANCHILDES with regular expressions

5 matches in 5 utterances

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

  1. shall we make a burger ? MOT · eng_british_Manchester_II/nic05b.cha, line 918 · Nicole 2;02
  2. shall we make a burger up for dolly ? MOT · eng_british_Manchester_II/nic05b.cha, line 920 · Nicole 2;02
  3. do you think dolly would like a burger ? MOT · eng_british_Manchester_II/nic05b.cha, line 922 · Nicole 2;02
  4. she'll have to have her burger cheeseless . MOT · eng_british_Manchester_II/nic05b.cha, line 957 · Nicole 2;02
  5. maybe Co_co would like some burger . MOT · eng_british_Manchester_II/nic05b.cha, line 970 · Nicole 2;02
  1. eng_british_Manchester_II/nic05b.cha, line 918 · Nicole, 2;2.05
    CHIxxx .
    MOTwe can't hear you with that piece of cheese stuck in your mouth .
    MOT*MOT: shall we make a burger ?
    MOTshall we make a burger up for dolly ?
    MOTdo you think dolly would like a burger ?
  2. eng_british_Manchester_II/nic05b.cha, line 920 · Nicole, 2;2.05
    MOTwe can't hear you with that piece of cheese stuck in your mouth .
    MOTshall we make a burger ?
    MOT*MOT: shall we make a burger up for dolly ?
    MOTdo you think dolly would like a burger ?
    MOTthere .
  3. eng_british_Manchester_II/nic05b.cha, line 922 · Nicole, 2;2.05
    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 .
  4. eng_british_Manchester_II/nic05b.cha, line 957 · Nicole, 2;2.05
    MOTput the cheese on there ?
    MOTno ?
    MOT*MOT: she'll have to have her burger cheeseless .
    MOTgo on .
    MOTxxx .
  5. eng_british_Manchester_II/nic05b.cha, line 970 · Nicole, 2;2.05
    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 .

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_II2.44
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/nic05b.chaNicole 2;2.052,049552.44

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. burger5 · 100.0%