PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

3.41 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (531 utterances, 2,054 words searched).

  1. hmm ? MOT · eng_british_Manchester_II/nic07a.cha, line 95 · Nicole 2;02
  2. hmm ? MOT · eng_british_Manchester_II/nic07a.cha, line 1078 · Nicole 2;02
  3. hmm ? MOT · eng_british_Manchester_II/nic07a.cha, line 1204 · Nicole 2;02
  4. hmm ? MOT · eng_british_Manchester_II/nic07a.cha, line 1210 · Nicole 2;02
  5. hmm ? MOT · eng_british_Manchester_II/nic07a.cha, line 1225 · Nicole 2;02
  6. hmm ? MOT · eng_british_Manchester_II/nic07a.cha, line 1261 · Nicole 2;02
  7. hmm ? MOT · eng_british_Manchester_II/nic07a.cha, line 1323 · Nicole 2;02
  1. eng_british_Manchester_II/nic07a.cha, line 95 · Nicole, 2;2.27
    MOTshould be in your bed+room .
    MOTare you thirsty ?
    MOT*MOT: hmm ?
    MOTare you thirsty girl ?
    MOTyou haven't told Caroline where you went last week .
  2. eng_british_Manchester_II/nic07a.cha, line 1078 · Nicole, 2;2.27
    MOTcan you read us another one ?
    CHIyeah .
    MOT*MOT: hmm ?
    CHIoh .
    CHIPostman_Pat Jess_cat and [/] and Goggin .
  3. eng_british_Manchester_II/nic07a.cha, line 1204 · Nicole, 2;2.27
    CHIno .
    MOTwhy do you get like this ?
    MOT*MOT: hmm ?
    MOTxxx .
    MOTxxx all xxx .
  4. eng_british_Manchester_II/nic07a.cha, line 1210 · Nicole, 2;2.27
    MOTxxx .
    MOTxxx all xxx .
    MOT*MOT: hmm ?
    MOTno ?
    MOThow many books have we got ?
  5. eng_british_Manchester_II/nic07a.cha, line 1225 · Nicole, 2;2.27
    CHIno .
    MOTcan't you see them ?
    MOT*MOT: hmm ?
    MOTone two three four five six .
    CHImmhm .
  6. eng_british_Manchester_II/nic07a.cha, line 1261 · Nicole, 2;2.27
    MOTmmhm ?
    MOTdo you want to come and sit on my knee and go to sleep ?
    MOT*MOT: hmm ?
    MOTwant to come sit on my knee and go to sleep ?
    CHILucy is coming later .
  7. eng_british_Manchester_II/nic07a.cha, line 1323 · Nicole, 2;2.27
    MOTyou should learn something new everyday .
    MOTyou've learnt to say tomorrow , haven't you ?
    MOT*MOT: hmm ?
    CHImmhm .
    INVhello .

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_II3.41
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/nic07a.chaNicole 2;2.272,054773.41

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. hmm7 · 100.0%