PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

3.82 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (425 utterances, 1,572 words searched).

  1. an h@l . GLO · eng_USA_Brown/sarah056.cha, line 220 · Sarah 3;04
  2. an h@l . GLO · eng_USA_Brown/sarah056.cha, line 223 · Sarah 3;04
  3. here # let's make an eight # an h@l . GLO · eng_USA_Brown/sarah056.cha, line 228 · Sarah 3;04
  4. is that what you mean # an h@l ? GLO · eng_USA_Brown/sarah056.cha, line 230 · Sarah 3;04
  5. that's an h@l # yeah . MOT · eng_USA_Brown/sarah056.cha, line 311 · Sarah 3;04
  6. what can an h@l do ? GLO · eng_USA_Brown/sarah056.cha, line 319 · Sarah 3;04
  1. eng_USA_Brown/sarah056.cha, line 220 · Sarah, 3;4.01
    CHIgot stay in the box .
    MOTon top the toy box .
    GLO*GLO: an h@l .
    GLOan h@l .
    CHIno # it's not .
  2. eng_USA_Brown/sarah056.cha, line 223 · Sarah, 3;4.01
    MOTon top the toy box .
    GLOan h@l .
    GLO*GLO: an h@l .
    CHIno # it's not .
    GLOhere # let's make an eight # an h@l .
  3. eng_USA_Brown/sarah056.cha, line 228 · Sarah, 3;4.01
    GLOan h@l .
    CHIno # it's not .
    GLO*GLO: here # let's make an eight # an h@l .
    GLOis that what you mean # an h@l ?
    MOTno .
  4. eng_USA_Brown/sarah056.cha, line 230 · Sarah, 3;4.01
    CHIno # it's not .
    GLOhere # let's make an eight # an h@l .
    GLO*GLO: is that what you mean # an h@l ?
    MOTno .
    CHII get my alphabet .
  5. eng_USA_Brown/sarah056.cha, line 311 · Sarah, 3;4.01
    CHIan h@l .
    CHIand an h@l # right dere .
    MOT*MOT: that's an h@l # yeah .
    CHIwhat an h@l right dere .
    MOTdid you find it ?
  6. eng_USA_Brown/sarah056.cha, line 319 · Sarah, 3;4.01
    MOTdid you find it ?
    GLOdid you find it ?
    GLO*GLO: what can an h@l do ?
    MOTwhat's that one ?
    GLObet it can stand up .

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_Brown3.82
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah056.chaSarah 3;4.011,572663.82

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. h6 · 100.0%