49
General characteristics of transcriptions by EXMARaLDA are described
by Rehbein (2011) as follows:
(1)
“spoken language (discourse) is transformed in a written form in
score areas abbreviated as ‘partiturs’;
(2)
the multiparty discourse with its diverse speakers is ordered along
‘tiers’ and not along the lines we are familiar of a written/printed text or text
program;
(3)
all tiers within a partitur follow the rules of simultaneity of their
representation;
The illustration presented below illustrates the general characteristics of
EXMARaLDA.
Three score areas [=partiturs] with (automatically processed) numbering on the
left, above
speakers tier (of speaker Serkan) tier (of speaker Serkan)
[12]
. .
28 [01:03.5]
29 [01:04.1]
30 [01:06.1]
SERKAN [v]
Testereydi ya !
H
!
SERKAN(eng) [v]
ya !
KAAN [v]
Testere?
KAAN(eng) [v]
Saw?
AHMET [v]
Kendi dilinde söylerse sorun yok.
AHMET(eng) [v]
If he replies in his mother tongue, it is not a problem.
translation tiers
Figure 5: Main
characteristics of EXMARaLDA
50
(4)
a time line above the partitur indicates the absolute points of time
following one after each other which are not to be mistaken as a numbering of
utterance segments;
(5)
an utterance related translation is an utterance-by-utterance
translation written into the tier(s) immediately under the tier of the original,
authentic utterance (:sublinear)” (p. 2).
General signal types of interjections of Turkish native speakers are
classified based on Rehbein & Romaniuk’s (in print) signal categories of H’s parts
of ‘Communicative Apparatus’ (CA) by means of which they studied three
Slavonic languages: Russian, Polish and Ukranian as presented in Figure 6. In this
study, interjections are analyzed under the following headings:
Understanding
(All stages of understanding are accomplished by H), Misunderstanding (In this
class, adoption of S’s plan by and formation of t e ’s plan are wrongly
accomplished, i.e. H activates wrong knowledge on the basis of wrongly perceived
speech actions), Believing to understand (Continuing the discourse without
confidence t at understanding is correct), Guessing Realized by ’s ec o
questions, explicit hypotheses, queries etc. to make sure that previous
understanding is correct), Partial understanding (H runs through some stages of
understanding but does not adopt S’s plan and/or does not form an own ’s
plan), Non-understanding(H signalizes non-compre ension of speakers’
utterances).
Rehbein and Romaniuk’s (in print) classes of H’s signals used for
categorizing H’s parts of ‘Communicative Apparatus’ was used to interpret the
language constellation.
51
Figure 6: Classes of Hearer’s signals used for categorizing H’s part of
‘Communicative Apparatus’ (Rehbein & Romaniuk, in print)
3.6.2. Phonological Analysis Software (PRAAT)
Interjections uttered by Turkish and Azerbaijani native speakers were
analyzed with a computer program named as PRAAT which is a software package
designed by Paul Boersma and David Weenik at the University of Amsterdam to
help the linguists use in phonetic and phonological research. PRAAT was utilized
so as to analyze the prosodic dimension (with its main parameters of duration,
pitch contour and intensity) of the interjections.
In
the sample below, in the upper section
the intensity
52
Figure 7: PRAAT
Analysis Sample
Intensity
waveform
Blue line
shows the
pitch
contour
while
yellow line
indicates the
average
pitch
contour.
Duration can be followed with the numerical indicators at the bottom.
53
CHAPTER 4
DATA ANALYSIS AND INTERPRETATION OF RESULTS
4.0. Presentation
This chapter presents the analysis of the results in sequence with the
research questions of the study. Firstly, a brief description of the analyzed data is
given. Secondly, forms and functions of interjections used by Turkish native
speakers in the data are presented following the forms and functions of
interjections used by Azerbaijani native speakers. Lastly, comparative
interpretation of the forms and functions of interjections used by Turkish and
Azerbaijani native speakers in order to signal understanding is presented.
4.1. A Brief Description of the Data
Three whole sessions of the taboo game played by Turkish and
Azerbaijani were video recorded for the analysis. There are circa two hours of
data in total.
There are three sets of data circa two hours in total. Each set of video-
recorded Taboo game session is circa 30 minutes. However camera split two
Taboo game sessions into halves.
The data collected through video recordings from Turkish and Azerbaijani
native speakers were transcribed with EXMARaLDA (Extensible Markup
Language for Discourse Annotation).