PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

2.44 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (562 utterances, 2,866 words searched).

  1. let's have the blue ones . MOT · eng_british_Manchester_I/aran20b.cha, line 172 · Aran 2;05
  2. let's put this dress on . MOT · eng_british_Manchester_I/aran20b.cha, line 1238 · Aran 2;05
  3. let's stick the back together . MOT · eng_british_Manchester_I/aran20b.cha, line 1327 · Aran 2;05
  4. <shall we> [//] let's find the socks then . MOT · eng_british_Manchester_I/aran20b.cha, line 1522 · Aran 2;05
  5. let's put those <on on> [/] on dolly . MOT · eng_british_Manchester_I/aran20b.cha, line 1534 · Aran 2;05
  6. let's play with the train . MOT · eng_british_Manchester_I/aran20b.cha, line 1755 · Aran 2;05
  7. let's make it into a circus train . MOT · eng_british_Manchester_I/aran20b.cha, line 1757 · Aran 2;05
  1. MOTthat means it's red hot .
    MOTcome on .
    MOT*MOT: let's have the blue ones .
    MOTcan you find me a blue one like that ?
    CHI<want want> [//] <I want> [/] I want have one those again .
  2. MOTdon't take +//.
    MOTshe'll be cold if you do that .
    MOT*MOT: let's put this dress on .
    CHI<no no no no> [/] no .
    MOTand then I can pretend I've got a little girl ,, can't I ?
  3. MOTdolly's got bare toes ,, has she ?
    MOTwell come on .
    MOT*MOT: let's stick the back together .
    CHIand this on .
    MOTand that one as well ?
  4. INVshe's got bare toes yeah .
    CHIput the sock on .
    MOT*MOT: <shall we> [//] let's find the socks then .
    MOThere we are .
    MOTthere's one .
  5. MOTthere's the other one .
    MOTcome on .
    MOT*MOT: let's put those <on on> [/] on dolly .
    MOT<shall we give> [/] shall we give dolly a name ?
    MOThmm ?
  6. MOTcome on Mister_silly .
    MOTcome on .
    MOT*MOT: let's play with the train .
    MOTlet's make it into a circus train .
    MOTcome on .
  7. MOTcome on .
    MOTlet's play with the train .
    MOT*MOT: let's make it into a circus train .
    MOTcome on .
    MOTare you up to your usual silly tricks ?

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. Aran eng_british_Manchester_I2.44
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/aran20b.chaAran 2;5.242,866772.44

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. let's7 · 100.0%