PHPCLANCHILDES with regular expressions

4 matches in 4 utterances

2.73 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (327 utterances, 1,466 words searched).

  1. here # Ann_Marie . MOT · eng_USA_Brown/sarah097.cha, line 16 · Sarah 4;02
  2. Ann_Marie # don't do that . MOT · eng_USA_Brown/sarah097.cha, line 238 · Sarah 4;02
  3. gonna baby+sit today # Ann_Marie ? MOT · eng_USA_Brown/sarah097.cha, line 247 · Sarah 4;02
  4. who took care of you last night # Ann_Marie ? MOT · eng_USA_Brown/sarah097.cha, line 344 · Sarah 4;02
  1. CHII have a whole lot .
    MOT*MOT: here # Ann_Marie .
    ANNthank+you .
    CHI<le(t) me see> [/] # <le(t) me see> [/] # le(t) me see just the same .
  2. CHImake it like that .
    MELwell that's new since I was little .
    MOT*MOT: Ann_Marie # don't do that .
    MOTleave it alone .
    CHIdon't do that # I'm looking at it .
  3. CHIdon't do that # I'm looking at it .
    CHIle(t) me see it .
    MOT*MOT: gonna baby+sit today # Ann_Marie ?
    MOTmy baby+sitter .
    CHII'm almost as +...
  4. ANNyou have to touch up here .
    ANNgo ahead # do it .
    MOT*MOT: who took care of you last night # Ann_Marie ?
    MOTLinda .
    MOTLinda ?

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_Brown2.73
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah097.chaSarah 4;2.231,466442.73

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. ann_marie4 · 100.0%