PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

2.74 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (679 utterances, 2,192 words searched).

  1. I'm going to cut some cakes out . MOT · eng_british_Manchester_II/nic11a.cha, line 161 · Nicole 2;04
  2. going to cut some cakes out ? MOT · eng_british_Manchester_II/nic11a.cha, line 170 · Nicole 2;04
  3. how many cakes have you got there ? MOT · eng_british_Manchester_II/nic11a.cha, line 174 · Nicole 2;04
  4. how many cakes have you done ? MOT · eng_british_Manchester_II/nic11a.cha, line 178 · Nicole 2;04
  5. how many cakes ? MOT · eng_british_Manchester_II/nic11a.cha, line 182 · Nicole 2;04
  6. we've got some shapes and we've got some cakes . MOT · eng_british_Manchester_II/nic11a.cha, line 445 · Nicole 2;04
  1. eng_british_Manchester_II/nic11a.cha, line 161 · Nicole, 2;4.18
    MOTwww .
    MOTNicole .
    MOT*MOT: I'm going to cut some cakes out .
    MOTare you going to help me ?
    MOToh right .
  2. eng_british_Manchester_II/nic11a.cha, line 170 · Nicole, 2;4.18
    MOToh right .
    CHIcut it .
    MOT*MOT: going to cut some cakes out ?
    MOTthere .
    MOThow many cakes have you got there ?
  3. eng_british_Manchester_II/nic11a.cha, line 174 · Nicole, 2;4.18
    MOTgoing to cut some cakes out ?
    MOTthere .
    MOT*MOT: how many cakes have you got there ?
    MOTdo you know ?
    MOThow many cakes have you done ?
  4. eng_british_Manchester_II/nic11a.cha, line 178 · Nicole, 2;4.18
    MOThow many cakes have you got there ?
    MOTdo you know ?
    MOT*MOT: how many cakes have you done ?
    MOTNicole .
    MOThow many cakes ?
  5. eng_british_Manchester_II/nic11a.cha, line 182 · Nicole, 2;4.18
    MOThow many cakes have you done ?
    MOTNicole .
    MOT*MOT: how many cakes ?
    MOThello .
    CHIxxx here .
  6. eng_british_Manchester_II/nic11a.cha, line 445 · Nicole, 2;4.18
    MOTand what're we going to put out next ?
    CHIxxx .
    MOT*MOT: we've got some shapes and we've got some cakes .
    MOThmm ?
    CHIright .

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_II2.74
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/nic11a.chaNicole 2;4.182,192662.74

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. cakes6 · 100.0%