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

Wed Nov 18 14:59:09 UTC 2015

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 <chibolts at googlegroups.com<mailto:chibolts at googlegroups.com>> on behalf of Alex CRISTIA <alecristia at gmail.com<mailto:alecristia at gmail.com>>
Reply-To: ChiBolts <chibolts at googlegroups.com<mailto:chibolts at googlegroups.com>>
Date: Wednesday, November 18, 2015 at 3:31 AM
To: ChiBolts <chibolts at googlegroups.com<mailto:chibolts at googlegroups.com>>
Cc: Celia Rosemberg <crrosem at hotmail.com<mailto:crrosem at hotmail.com>>, gladys <gladys.ojea at gmail.com<mailto:gladys.ojea at gmail.com>>, Alejandra Stein <alejandrastein at yahoo.com.ar<mailto:alejandrastein at yahoo.com.ar>>
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]):

[https://ssl.gstatic.com/ui/v1/icons/mail/images/cleardot.gif]

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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