accurate utterance and turn counts taking into account linguistic, verbal, and non-verbal contributi

Fri Nov 20 07:27:55 UTC 2015

Dear Brian,

Sorry that my question isn't clear. The hope is to be able to *separate* 
the different types; i.e. apply one processing scheme and get, for the 
child:
- 1 non-verbal turn (pointing), 

Run a different analysis and get, for the child:
- 1 verbal non-linguistic turn (&baba), 

Run a different analysis and get, for the child:
- 1 linguistic turn ("baby")

Regular MLT groups all together, as you point out.

Thank you very much,

Alex

On Wednesday, November 18, 2015 at 3:59:11 PM UTC+1, Brian MacWhinney wrote:
>
> Dear Alex,
>      As far as I can see, MLT is doing what you want.  Running on your six 
> line sample, I get three turns for the child.  It is true that it is not 
> necessary to include the [+ trn] postcode.  I’ll fix that part of the 
> manual.
>
> —Brian MacWhinney
>
> From: ChiBolts <chib... at googlegroups.com <javascript:>> on behalf of Alex 
> CRISTIA <alecr... at gmail.com <javascript:>>
> Reply-To: ChiBolts <chib... at googlegroups.com <javascript:>>
> Date: Wednesday, November 18, 2015 at 3:31 AM
> To: ChiBolts <chib... at googlegroups.com <javascript:>>
> Cc: Celia Rosemberg <crr... at hotmail.com <javascript:>>, gladys <
> glady... at gmail.com <javascript:>>, Alejandra Stein <
> alejand... at yahoo.com.ar <javascript:>>
> Subject: accurate utterance and turn counts taking into account 
> linguistic, verbal, and non-verbal contributi
>
> Dear Chibolters,
>
> We would like to have separate counts for both utterances and turns, 
> taking into account linguistic, verbal, and non-verbal contributions. For 
> example:
>
> *CHI: 0. 
> %act: points to a cookie
> *MOT: okay . 
> *CHI: &baba .
> *MOT: go for it .
> *CHI: baby .
>
> We see in this example:
> - 3 turns by the child: 1 non-verbal (pointing), 1 verbal non-linguistic 
> (&baba), and 1 linguistic (baby); 
> - 2 utterances by the child (because utterances cannot be non-verbal): 1 
> verbal non-linguistic (&baba), and 1 linguistic (baby)
>
> MLT on the sample above yields 3 utterances and 3 turns. If we MOR it and 
> MLU the output, then we find 1 utterance. Is there a simple way to extract 
> the other subtypes? Or should we add by hand codes such as:
>
> *CHI: 0. [- verbal]
> %act: points to a cookie
> %trn: $TUR
> *MOT: okay . 
> *CHI: &baba .
> *MOT: go for it .
> *CHI: baby . 
>
> To exclude non-verbal turns from MLT:
> > MLT -s"[- verbal]"  @    
> mlt -s"[- verbal]" @
> Fri Oct 30 09:57:59 2015
> mlt (17-Apr-2015) is conducting analyses on:
>   ALL speaker tiers
> ****************************************
> From file </Users/alejandrastein/Desktop/prueba.cha>
> MLT for Speaker: *CHI:
>   MLT (xxx, yyy and www are EXCLUDED from the word counts, but are 
> INCLUDED in utterance counts):
>     Number of: utterances = 2, turns = 2, words = 1
> Ratio of words over turns = 0.500
> Ratio of utterances over turns = 1.000
> Ratio of words over utterances = 0.500
>
> To count only non-verbal turns:
> > keymap +b$TUR* +t%trn  @   
> keymap +b$tur* +t%trn @
> Fri Oct 30 09:59:12 2015
> keymap (17-Apr-2015) is conducting analyses on:
>   ALL speaker tiers
> and those speakers' ONLY dependent tiers matching: %TRN;
> ****************************************
> From file </Users/alejandrastein/Desktop/prueba.cha>
> Speaker *CHI:
>   Key word "$tur" found 1 time
>
> Incidentally, the CLAN manual does refer to non-verbal turns twice; on p. 
> 34:
>
> *5.4 MLT Analysis *
>
> *The third analysis we will perform is to compute MLT (Mean Length of 
> Turn) for both child and mother. Note that, unlike the MLU program, the 
> CLAN program MLT includes the symbols xxx and yyy in all counts. Thus, 
> utterances that consist of only unintelligible vocal material still 
> constitute turns, as do nonverbal turns indicated by the postcode [+ trn] 
> as illustrated in the following example: *
>
>
>
> **CHI: 0.[+ trn] %gpx: CHI points to picture in book *
>
> *We can use a single command to run our complete analysis and put all the 
> results into a single file. *
>
>
> *mlt *.cha > allmlt.cex *
>
>
> However, as far as we can see, with or without [+ trn] one gets the same 
> results using the example provided in the manual (**CHI: 0.[+ trn]*):
>
> *WITH TRN*
>
> > mlt  @
> mlt @
> Fri Nov 13 09:37:51 2015
> mlt (09-Sep-2015) is conducting analyses on:
>   ALL speaker tiers
> ****************************************
> From file </Users/acristia/Dropbox/ANR_argentina/transcriptions/test.cha>
> MLT for Speaker: *CHI:
>   MLT (xxx, yyy and www are EXCLUDED from the word counts, but are 
> INCLUDED in utterance counts):
>     Number of: utterances = 1, turns = 1, words = 0
>     Ratio of words over turns = 0.000
>     Ratio of utterances over turns = 1.000
>     Ratio of words over utterances = 0.000
>
>
> *WITHOUT TRN (i.e., I removed [+ trn] from **0.[+ trn]*)
>
> > mlt  @
> mlt @
> Fri Nov 13 09:38:32 2015
> mlt (09-Sep-2015) is conducting analyses on:
>   ALL speaker tiers
> ****************************************
> From file </Users/acristia/Dropbox/ANR_argentina/transcriptions/test.cha>
> MLT for Speaker: *CHI:
>   MLT (xxx, yyy and www are EXCLUDED from the word counts, but are 
> INCLUDED in utterance counts):
>     Number of: utterances = 1, turns = 1, words = 0
>     Ratio of words over turns = 0.000
>     Ratio of utterances over turns = 1.000
>     Ratio of words over utterances = 0.000
>
>
> Thank you all in advance for your help,
> Alex Cristia
>
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