PHPCLANCHILDES with regular expressions

4 matches in 4 utterances

2.86 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (388 utterances, 1,399 words searched).

  1. what else are we gonna buy ? MOT · eng_USA_Brown/sarah032.cha, line 452 · Sarah 2;10
  2. um # what else . MOT · eng_USA_Brown/sarah032.cha, line 1056 · Sarah 2;10
  3. what else did you have ? MOT · eng_USA_Brown/sarah032.cha, line 1058 · Sarah 2;10
  4. ice+cream # and # tonic # and what else ? MOT · eng_USA_Brown/sarah032.cha, line 1062 · Sarah 2;10
  1. eng_USA_Brown/sarah032.cha, line 452 · Sarah, 2;10.05
    CHIum # toy(s) .
    MOTtoys ?
    MOT*MOT: what else are we gonna buy ?
    CHIuh cups .
    MOTwhat ?
  2. eng_USA_Brown/sarah032.cha, line 1056 · Sarah, 2;10.05
    MOTwhat'd you have to eat at the circus ?
    CHIice+cream .
    MOT*MOT: um # what else .
    MOTwhat else did you have ?
    CHI0 .
  3. eng_USA_Brown/sarah032.cha, line 1058 · Sarah, 2;10.05
    CHIice+cream .
    MOTum # what else .
    MOT*MOT: what else did you have ?
    CHI0 .
    MOTice+cream # and # tonic # and what else ?
  4. eng_USA_Brown/sarah032.cha, line 1062 · Sarah, 2;10.05
    MOTwhat else did you have ?
    CHI0 .
    MOT*MOT: ice+cream # and # tonic # and what else ?
    CHIand a tonic .
    MOTum .

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. Sarah eng_USA_Brown2.86
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah032.chaSarah 2;10.051,399442.86

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. else4 · 100.0%