PHPCLANCHILDES with regular expressions

6 matches in 5 utterances

2.93 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (457 utterances, 2,050 words searched).

  1. you want to make your toes and fingers , do you ? MOT · eng_british_Manchester_II/warr28a.cha, line 31 · Warren 2;07
  2. are you going to make pink toes or yellow toes ? MOT · eng_british_Manchester_II/warr28a.cha, line 44 · Warren 2;07
  3. are you going to make pink toes or yellow toes ? MOT · eng_british_Manchester_II/warr28a.cha, line 44 · Warren 2;07
  4. you take off your shoes and socks and we can make your toes , can't we ? MOT · eng_british_Manchester_II/warr28a.cha, line 51 · Warren 2;07
  5. you could do a little prod where each of your toes are . MOT · eng_british_Manchester_II/warr28a.cha, line 229 · Warren 2;07
  6. how many toes have you got on that foot ? MOT · eng_british_Manchester_II/warr28a.cha, line 255 · Warren 2;07
  1. CHII put the shapes on .
    CHIwant to make my toes and fingers .
    MOT*MOT: you want to make your toes and fingers , do you ?
    MOTnow these .
    MOT<we must> [//] we really ought to wash these sheets because they're getting all sticky .
  2. MOT<we must> [//] we really ought to wash these sheets because they're getting all sticky .
    MOTyou take off your shoes and socks then .
    MOT*MOT: are you going to make pink toes or yellow toes ?
    CHIpink toes .
    MOTokay .
  3. CHIpink toes .
    MOTokay .
    MOT*MOT: you take off your shoes and socks and we can make your toes , can't we ?
    CHIin shoes .
    MOTno .
  4. MOToh .
    MOTyou prodded your foot .
    MOT*MOT: you could do a little prod where each of your toes are .
    MOTone two three four five .
    CHIand a toe there .
  5. CHIwant Nana cut it bath time .
    MOTokay .
    MOT*MOT: how many toes have you got on that foot ?
    CHIone two three four little ones .
    CHIand a big one .

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. Warren eng_british_Manchester_II2.93
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/warr28a.chaWarren 2;7.122,050562.93

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. toes6 · 100.0%