PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

5.82 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (335 utterances, 1,375 words searched).

  1. could you tell me a story about Bugs ? KEN · eng_USA_Brown/sarah051.cha, line 246 · Sarah 3;03
  2. she's about ten . KEN · eng_USA_Brown/sarah051.cha, line 312 · Sarah 3;03
  3. tell me about dancing school . KEN · eng_USA_Brown/sarah051.cha, line 513 · Sarah 3;03
  4. what about dancing school ? KEN · eng_USA_Brown/sarah051.cha, line 532 · Sarah 3;03
  5. tell me about her . KEN · eng_USA_Brown/sarah051.cha, line 654 · Sarah 3;03
  6. tell me about Yuna . KEN · eng_USA_Brown/sarah051.cha, line 679 · Sarah 3;03
  7. tell me about Yuna and Bugs . KEN · eng_USA_Brown/sarah051.cha, line 684 · Sarah 3;03
  8. ya have ta think about it though . MOT · eng_USA_Brown/sarah051.cha, line 1143 · Sarah 3;03
  1. CHIyou(rs) # you .
    MOToh # alright .
    KEN*KEN: could you tell me a story about Bugs ?
    KENwhat did Bugs do on tv .
    CHIum # xxx .
  2. KENoh # Millisandy's real old .
    KENMillisandy was Jo_ann's before he was yours <and she's> [/] and she's ten .
    KEN*KEN: she's about ten .
    CHII wan(t) a ice+cweam [: ice+cream] .
    MOTthere isn't any .
  3. KENok # as soon as you finish your ice+cream .
    CHIthe(r)e .
    KEN*KEN: tell me about dancing school .
    CHIwhen .
    KENlast week .
  4. MOTyeah you were here last week .
    KENhmm .
    KEN*KEN: what about dancing school ?
    KENwhat did you do ?
    CHII dance .
  5. MOTwhere'd ya ever come up with that name ?
    KENis she a rabbit ?
    KEN*KEN: tell me about her .
    CHIyyy .
    MOTPetunia # isn't that his girl+friend's name .
  6. MOTPetunia # Petunia .
    CHIPetunia .
    KEN*KEN: tell me about Yuna .
    CHIhmm .
    KENtell me about Yuna and Bugs .
  7. KENtell me about Yuna .
    CHIhmm .
    KEN*KEN: tell me about Yuna and Bugs .
    MOTwhere do they go ?
    MOTthey go dancin(g) ?
  8. KENis that what she's doing ?
    CHIyyy .
    MOT*MOT: ya have ta think about it though .
    KENwhere did you learn to do that ?
    CHIuh # well my # monkey # do that .

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_Brown5.82
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/sarah051.chaSarah 3;3.071,375885.82

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. about8 · 100.0%