PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

3.98 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (438 utterances, 1,507 words searched).

  1. oh # we'll have to get it today . MOT · eng_USA_Brown/sarah059.cha, line 80 · Sarah 3;04
  2. we'll get it after dancin(g) school . MOT · eng_USA_Brown/sarah059.cha, line 82 · Sarah 3;04
  3. tomorrow we'll go ta Waltham to see Santa_Claus . MOT · eng_USA_Brown/sarah059.cha, line 719 · Sarah 3;04
  4. we'll get all dressed up pretty . MOT · eng_USA_Brown/sarah059.cha, line 731 · Sarah 3;04
  5. we'll see him over at Nana's house . MOT · eng_USA_Brown/sarah059.cha, line 1265 · Sarah 3;04
  6. we'll have lots o(f) fun . MOT · eng_USA_Brown/sarah059.cha, line 1281 · Sarah 3;04
  1. eng_USA_Brown/sarah059.cha, line 80 · Sarah, 3;4.26
    CHIsomeone e(l)se did .
    MOTyou forgot it ?
    MOT*MOT: oh # we'll have to get it today .
    MOTwe'll get it after dancin(g) school .
    MOTok ?
  2. eng_USA_Brown/sarah059.cha, line 82 · Sarah, 3;4.26
    MOTyou forgot it ?
    MOToh # we'll have to get it today .
    MOT*MOT: we'll get it after dancin(g) school .
    MOTok ?
    CHIyep .
  3. eng_USA_Brown/sarah059.cha, line 719 · Sarah, 3;4.26
    MOThe said he might be there .
    MOTbut if he's not there # he'll see ya tomorrow in Waltham .
    MOT*MOT: tomorrow we'll go ta Waltham to see Santa_Claus .
    MOTyou # with me (a)n(d) Daddy .
    MOTok ?
  4. eng_USA_Brown/sarah059.cha, line 731 · Sarah, 3;4.26
    CHIalright .
    MOTok .
    MOT*MOT: we'll get all dressed up pretty .
    MOThuh ?
    MOTso you can have your picture taken with Santa_Claus (a)n(d) you can tell him what you want .
  5. eng_USA_Brown/sarah059.cha, line 1265 · Sarah, 3;4.26
    MOTyeah .
    CHIwhere ?
    MOT*MOT: we'll see him over at Nana's house .
    MOT(be)cause we're gonna have supper over at Nana's .
    MOTme and you .
  6. eng_USA_Brown/sarah059.cha, line 1281 · Sarah, 3;4.26
    CHIyeah .
    MOTyeah .
    MOT*MOT: we'll have lots o(f) fun .
    CHIxxx .
    CHIthat was on the table .

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_Brown3.98
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah059.chaSarah 3;4.261,507663.98

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. we'll6 · 100.0%