PHPCLANCHILDES with regular expressions

7 matches in 7 utterances

3.93 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (470 utterances, 1,782 words searched).

  1. mmm . MOT · eng_british_Manchester_II/warr05b.cha, line 235 · Warren 1;11
  2. mmm . MOT · eng_british_Manchester_II/warr05b.cha, line 294 · Warren 1;11
  3. mmm . MOT · eng_british_Manchester_II/warr05b.cha, line 472 · Warren 1;11
  4. mmm . MOT · eng_british_Manchester_II/warr05b.cha, line 480 · Warren 1;11
  5. mmm . INV · eng_british_Manchester_II/warr05b.cha, line 486 · Warren 1;11
  6. mmm sounds like a tasty meal . MOT · eng_british_Manchester_II/warr05b.cha, line 594 · Warren 1;11
  7. mmm . MOT · eng_british_Manchester_II/warr05b.cha, line 598 · Warren 1;11
  1. eng_british_Manchester_II/warr05b.cha, line 235 · Warren, 1;11.26
    MOTit probably is yes .
    CHIin cup .
    MOT*MOT: mmm .
    MOTI think I'll have this .
    MOTwhat is it ?
  2. eng_british_Manchester_II/warr05b.cha, line 294 · Warren, 1;11.26
    MOTmmhm .
    CHImmm .
    MOT*MOT: mmm .
    CHImmm .
    MOThere's a hotdog .
  3. eng_british_Manchester_II/warr05b.cha, line 472 · Warren, 1;11.26
    CHIMummy bite the cake .
    CHIMummy bite it .
    MOT*MOT: mmm .
    MOTthat's nice .
    CHImmm .
  4. eng_british_Manchester_II/warr05b.cha, line 480 · Warren, 1;11.26
    CHImmm .
    CHImmm .
    MOT*MOT: mmm .
    MOTI've had enough thank you .
    INVoh can I have some too ?
  5. eng_british_Manchester_II/warr05b.cha, line 486 · Warren, 1;11.26
    MOTI've had enough thank you .
    INVoh can I have some too ?
    INV*INV: mmm .
    INVthank you .
    MOTaren't you kind ?
  6. eng_british_Manchester_II/warr05b.cha, line 594 · Warren, 1;11.26
    MOTthe cabbage .
    MOTand an aubergine .
    MOT*MOT: mmm sounds like a tasty meal .
    MOTeggs cabbage and aubergine .
    MOTmmm .
  7. eng_british_Manchester_II/warr05b.cha, line 598 · Warren, 1;11.26
    MOTmmm sounds like a tasty meal .
    MOTeggs cabbage and aubergine .
    MOT*MOT: mmm .
    CHIeggs out .
    MOTeggs out yeah .

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_II3.93
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_II/warr05b.chaWarren 1;11.261,782773.93

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. mmm7 · 100.0%