PHPCLANCHILDES with regular expressions

9 matches in 9 utterances

25.50 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (90 utterances, 353 words searched).

  1. what am I doing now ? COL · eng_USA_Brown/eve08.cha, line 122 · Eve 1;09
  2. I see you . COL · eng_USA_Brown/eve08.cha, line 203 · Eve 1;09
  3. I see you . COL · eng_USA_Brown/eve08.cha, line 206 · Eve 1;09
  4. uhhuh # I know it is . MOT · eng_USA_Brown/eve08.cha, line 249 · Eve 1;09
  5. tapioca # I'm sorry there is no tapioca . MOT · eng_USA_Brown/eve08.cha, line 260 · Eve 1;09
  6. tomorrow I'll make some for you . MOT · eng_USA_Brown/eve08.cha, line 274 · Eve 1;09
  7. I'm sorry . MOT · eng_USA_Brown/eve08.cha, line 286 · Eve 1;09
  8. well I'm glad . MOT · eng_USA_Brown/eve08.cha, line 443 · Eve 1;09
  9. that's what I asked . MOT · eng_USA_Brown/eve08.cha, line 515 · Eve 1;09
  1. COLwill we turn the page in a minute ?
    COLwhat are we doing now ?
    COL*COL: what am I doing now ?
    CHIin a minute .
    COLm:hm .
  2. COLwhat do you see ?
    CHII see Fraser .
    COL*COL: I see you .
    COLI see you .
    COLwho do you see ?
  3. CHII see Fraser .
    COLI see you .
    COL*COL: I see you .
    COLwho do you see ?
    CHIxxx see Fraser .
  4. MOTalright .
    CHIthat Eve paper .
    MOT*MOT: uhhuh # I know it is .
    CHIthat Fraser paper .
    CHItapioca .
  5. CHIthat Fraser paper .
    CHItapioca .
    MOT*MOT: tapioca # I'm sorry there is no tapioca .
    CHIwant tapioca .
    MOTthere is no tapioca .
  6. MOTthere is no tapioca .
    CHIwant tap .
    MOT*MOT: tomorrow I'll make some for you .
    CHIwant tapioca lunch .
    CHIwant tapioca lunch .
  7. CHIwant tapioca lunch .
    MOTthere is no tapioca for lunch .
    MOT*MOT: I'm sorry .
    CHII ride a funny clown .
    CHIthat ?
  8. MOTare you happy now ?
    CHIyeah .
    MOT*MOT: well I'm glad .
    MOTstay happy for a little while # okay ?
    CHItapioca Eve lunch .
  9. CHIwhy not ?
    CHIwhy not ?
    MOT*MOT: that's what I asked .
    MOTwhy not ?
    CHIwhy ?

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. Eve eng_USA_Brown25.50
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_USA_Brown/eve08.chaEve 1;9.3539925.50

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. i9 · 100.0%