PHPCLANCHILDES with regular expressions

8 matches in 8 utterances

3.40 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (605 utterances, 2,355 words searched).

  1. there's a nest . MOT · eng_british_Manchester_I/anne25a.cha, line 164 · Anne 2;06
  2. there's Mr_A the apron man . MOT · eng_british_Manchester_I/anne25a.cha, line 967 · Anne 2;06
  3. there's Dippy_Duck all dressed up as a detective ,, isn't he ? MOT · eng_british_Manchester_I/anne25a.cha, line 1056 · Anne 2;06
  4. there's a Clever_Cat . MOT · eng_british_Manchester_I/anne25a.cha, line 1063 · Anne 2;06
  5. there's Dippy_Duck . MOT · eng_british_Manchester_I/anne25a.cha, line 1065 · Anne 2;06
  6. see if there's anything we missed . MOT · eng_british_Manchester_I/anne25a.cha, line 1154 · Anne 2;06
  7. there's his arms . MOT · eng_british_Manchester_I/anne25a.cha, line 1423 · Anne 2;06
  8. there's lots of Munching_Mikes in my name ,, isn't there ? MOT · eng_british_Manchester_I/anne25a.cha, line 1495 · Anne 2;06
  1. MOTcan you see a nest ?
    MOTmight not know what a nest looks like .
    MOT*MOT: there's a nest .
    MOTthat's it .
    CHIand where's the big nest ?
  2. MOTdo this picture ?
    MOTthese are the vowel men .
    MOT*MOT: there's Mr_A the apron man .
    MOTthink [//] there he is .
    MOTMr_E the magic man .
  3. MOTthere he is , look .
    CHIgolden xxx .
    MOT*MOT: there's Dippy_Duck all dressed up as a detective ,, isn't he ?
    CHIoh .
    CHIthere 0is [*] Clever_Cat .
  4. CHIoh .
    CHIthere 0is [*] Clever_Cat .
    MOT*MOT: there's a Clever_Cat .
    MOTthere's Dippy_Duck .
    CHIwant to xxx .
  5. CHIthere 0is [*] Clever_Cat .
    MOTthere's a Clever_Cat .
    MOT*MOT: there's Dippy_Duck .
    CHIwant to xxx .
    MOTpardon ?
  6. MOTwhat did +//.
    MOTlet's see if we drew all the right things .
    MOT*MOT: see if there's anything we missed .
    MOTwe drew the swings .
    MOTyou didn't think much of that ,, did you ?
  7. CHInose .
    MOTthat's lovely .
    MOT*MOT: there's his arms .
    CHIthere .
    MOTokay .
  8. MOTthere we are then .
    CHIMunching_Mike .
    MOT*MOT: there's lots of Munching_Mikes in my name ,, isn't there ?
    CHIyeah .
    CHIoh .

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. Anne eng_british_Manchester_I3.40
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
eng_british_Manchester_I/anne25a.chaAnne 2;6.292,355883.40

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. there's8 · 100.0%