PHPCLANCHILDES with regular expressions

6 matches in 6 utterances

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

  1. so we'll do two . MOT · eng_british_Manchester_II/warr28a.cha, line 108 · Warren 2;07
  2. so I'll make his egg in the middle at the front . MOT · eng_british_Manchester_II/warr28a.cha, line 940 · Warren 2;07
  3. so it needs a bit more hair on it . MOT · eng_british_Manchester_II/warr28a.cha, line 1003 · Warren 2;07
  4. so this has to be a little bit smaller , doesn't it ? MOT · eng_british_Manchester_II/warr28a.cha, line 1044 · Warren 2;07
  5. so who have we got ? MOT · eng_british_Manchester_II/warr28a.cha, line 1112 · Warren 2;07
  6. so which is the best ? MOT · eng_british_Manchester_II/warr28a.cha, line 1366 · Warren 2;07
  1. eng_british_Manchester_II/warr28a.cha, line 108 · Warren, 2;7.12
    CHIdo one foot .
    MOTwell we'll do two because I've made enough space for two .
    MOT*MOT: so we'll do two .
    CHII do one .
    MOTokay .
  2. eng_british_Manchester_II/warr28a.cha, line 940 · Warren, 2;7.12
    MOTan egg .
    MOTokay .
    MOT*MOT: so I'll make his egg in the middle at the front .
    CHIno [/] no .
    CHIwant to make a Daddy .
  3. eng_british_Manchester_II/warr28a.cha, line 1003 · Warren, 2;7.12
    CHIyeah .
    MOTokay .
    MOT*MOT: so it needs a bit more hair on it .
    MOTnot much more .
    MOTpoor Paul .
  4. eng_british_Manchester_II/warr28a.cha, line 1044 · Warren, 2;7.12
    CHIWarren .
    MOTWarren .
    MOT*MOT: so this has to be a little bit smaller , doesn't it ?
    MOTand with a little beady nose .
    MOTa nose just like a little bead stuck on .
  5. eng_british_Manchester_II/warr28a.cha, line 1112 · Warren, 2;7.12
    MOTand there's Warren .
    CHIlook at that .
    MOT*MOT: so who have we got ?
    CHIWarren and Mummy and Paul .
    MOTwhere's Mummy ?
  6. eng_british_Manchester_II/warr28a.cha, line 1366 · Warren, 2;7.12
    MOTlook at my nose .
    MOTit's gone all flat at the ends .
    MOT*MOT: so which is the best ?
    CHInothing .
    MOTwhich one do you like best ?

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;7.122,050662.93

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. so6 · 100.0%