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Research Journal of Social Sciences & Economics Review
Vol. 2, Issue 1, 2021 (January – March)
ISSN 2707-9023 (online), ISSN 2707-9015 (Print)
ISSN 2707-9015 (ISSN-L)
DOI: https://doi.org/10.36902/rjsser-vol2-iss1-2021(208-222)
____________________________________________________________________________________
___________________________________________________________________________
* Department of Applied Linguistics, Government College University, Faisalabad, Pakistan
Email: aalimalik381@gmail.com
** Department of Applied Linguistics, Government College University, Faisalabad, Pakistan
Email: ahmad453@yandex.com
*** Faculty of Arts and Social Sciences, Government College University, Faisalabad, Pakistan
Email: masimrai@gmail.com 208
RJSSER
Research Journal of Social
Sciences & Economics Review
Identification of Boosters as Metadiscourse across Punjabi and Urdu Languages: A
Machine Translation Approach
* Ali Raza Siddique, PhD Scholar
** Muhammad Ahmad, PhD Scholar (Corresponding Author)
*** Dr. Muhammad Asim Mahmood, Professor & Dean
__________________________________________________________________________________________
Abstract
Boosters are said to function appropriately as metadiscourse features across languages. This study,
therefore, aimed to investigate the functions and appropriateness of the metadiscourse features
across Punjabi and Urdu languages. For this purpose, a list of 79 boosters (as metadiscourse
features) was considered that (boosters) were first transliterated across Punjabi and Urdu languages
employing a machine translation process. Punjabi translation was carried through ‘Akhar’ (a
software), and Punjabi corpus (a tool). Whereas Urdu translation was realized through online Urdu
thesaurus, and ‘ijunoon’ (an online dictionary). Machine transliteration was followed by manual
cleansing of Punjabi and Urdu translated wordlists that helped identify boosters in the corpora.
Appropriateness of the identified boosters was then realized through expert opinion and Punjabi
corpus (for the Punjabi language), and expert opinion, online Urdu thesaurus, and Urdu WordNet
(for the Urdu language). This process further guided about how to; make wordlists, filter as well as
verify translated words, and offer interactional and interactive metadiscourse categories across
Punjabi and Urdu languages.
Keywords: Appropriateness of Metadiscourse Features; Identification of Boosters; Machine
Transliteration; Metadiscourse across Languages; Metadiscourse Functions
Introduction
Metadiscourse features are linguistic items that organize textual and interpersonal features across
different languages. This study is about boosters as metadiscourse category which incorporates
intensity into the text across Punjabi and Urdu languages. Many studies were conducted on
metadiscourse features across languages e.g. English, Thai (Bickner & Peyasantiwong, 1988),
Chinese (Zhang, 1990), Finnish (Mauranen, 1993; Tirkkonan-Condit, 1996), Japanese (Maynard,
1996), and Persian (Hashemi & Golparvar, 2012). But no significant attempt has been made on
metadiscourse features across Punjabi (i.e. Shahmukhi script) and Urdu languages. Thus, this study
(being the first attempt) explores metadiscourse features across Punjabi and Urdu languages through
machine translation.
Past studies (e.g. Bickner & Peyasantiwong, 1988; Hashemi & Golparvar, 2012; Mauranen,
1993; Maynard, 1996; Tirkkonan-Condit, 1996; Zhang, 1990) provide the taxonomy of metadiscourse
features that categorizes into interactive and interactional categories. The studies by Siddique,
Mahmood, and Iqbal (2018) and Siddique, Mahmood, Azhar, and Qasim (2018) proposed a
comprehensive taxonomy of boosters as metadiscourse features as per their interactive and
interactional categories. The said study is a significant source of inspiration for this study. The
developed list of boosters has never been studied across Punjabi and Urdu languages. Thus, this study
is going to be the first attempt to provide an awareness of boosters across Punjabi and Urdu
languages. Besides, this study introduces a new domain of studying, identifying, and functioning the
role of boosters across Punjabi and Urdu languages. In this way, this study outlines such issues as
have not been discussed before. As the main concern, this study focuses to see how boosters perform
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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209
functions across Punjabi and Urdu Languages. To answer this query, this study has identified boosters
across Punjabi and Urdu languages through machine translation. Thus, this study deals with the
development of boosters, the process of transliteration of boosters through the machine, the process of
cleansing the transliterated words as errors, and the process of mapping boosters across Punjabi and
Urdu languages. Keeping in view the aforementioned aims, this study speculates the following
research questions:
1. What boosters (as metadiscourse features) are transliterated across Punjabi and Urdu
Languages?
2. How boosters (as metadiscoursal features) are identified across Punjabi and Urdu Languages?
3. Which boosters (as metadiscoursal features) perform functions across Punjabi and Urdu
languages?
The interactional category is further divided into five sub-categories i.e. hedges, engagement
markers, relation markers, attitude markers, and boosters (Hyland, 2018). This study has delimited
metadiscourse features to its interactional category i.e. boosters. This study has only focused on
boosters.
Literature Review
This literature deals with several contributions that have been executed on metadiscourse features
across Punjabi and Urdu languages. Most of the studies have described metadiscourse features‟ utility
in real life. Many studies were seen on metadiscourse features across languages. But there is no
significant attempt has been made on metadiscourse features across Punjabi (i.e. Shahmukhi script)
and Urdu languages. Therefore, this study has attempted to examine boosters as a category of
metadiscourse across Punjabi and Urdu languages.
Punjabi Language
Different local or regional languages (e.g. Punjabi, Pashto, Sindhi, Saraiki, Urdu, and Balochi) are
used in Pakistan (Bhurgri, 2006). The Punjabi language has two dialects: (1) Eastern Punjabi which is
mostly spoken by the people of Punjab in India; and (2) Western Punjabi which is mostly spoken by
the people of Punjab in Pakistan (Kaur, Sharma, Preet & Bhatia, 2010; Narang, Sharma & Kumar,
2013; Sharma & Aarti, 2011). Perso-Arabic (Shahmukhi) script is used by the Pakistanis, and
Gurmukhi/Devanagari script is used by the Indians (Lehal & Saini, 2011; Malik, 2006; Virk,
Humayoun & Ranta, 2011).
The Punjabi language connects back with the Indo-Aryan languages (Gill & Lehal, 2008). But
with time, Persian, Arabic, and Turkish words constituted the Punjabi vocabulary. Also, there is a
problem with its alphabets i.e. there are no standardized alphabets in Punjabi. It is usually written by
using the alphabet of Urdu (Bhurgri, 2006). Punjabi (particularly spoken in Pakistan) is a less-
resourced language. Generally, very little work is done on Punjabi (Kaur, et al., 2010; Narang et al.,
2013). Moreover, Shahmukhi is written from right to left and is based on the Nastalique style of
Persian and Arabic script. The shape of the characters (in a word) is context-sensitive, which means a
letter has a different shape if it occurs at the start, middle, or end position of a word (Malik, 2006).
Urdu Language
Urdu () is written in the Persio-Arabic script and normally in Nastaliqb writing style (Hussain,
2004). It is a right-to-left script and the shape of its characters differs depending on its position in
words i.e. the shape of a character would be different in initial, middle, and end of word positions.
Urdu is written in bidirectional form i.e. letters are written from right-to-left and numbers from the
left-to-right format. Urdu is written with consonantal letters and aerabs. The vocalic content is
specified by using the aerab with letters. Aerab position can be on the top and bottom of a letter
(Adeeba & Hussain, 2011).
Machine Translation
The terms transliteration and transcription are often used as generic terms for various processes like
transliteration, transcription, romanization, transcribing, and technography (Halpern, 2002).
Transliteration is defined as “to write a word or letter in a different alphabet” (Halpern, 2002). It
denotes a process that maps one writing system into the other, ideally letter by letter. It attempts to
use a one-to-one grapheme correspondence (orthographic conversion). A good transliteration is a
reversible process to ensure that the source word can be regenerated from the target transliterated
word (Halpern, 2002). On the other hand, transcription is defined as a written representation of words
or music. In the words of Halpern (2002) “transcription is the representation of the source script of a
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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210
language in the target script in a manner that reflects the pronunciation of the original, often ignoring
graphemic (character-to-character) correspondences” (p. 2).
Metadiscourse Studies across Languages
The recent studies on metadiscourse across different languages have employed different research
methods. These studies are seen in different domains such as academic writing, book reviews, spoken
language, newspapers, and textbooks. The features of metadiscourse have been studied across
languages, genres, and disciplines. A very recent study on metadiscourse across language, Gholami,
Tajali, and Shokrpour (2014) investigated metadiscoursal features in English medical texts and their
Persian translations. This corpus-based study used a quantitative approach to present metadiscoursal
features in the data. To conduct the study, the researchers practiced different tools such as a taxonomy
of Hyland (2005) for data analysis; Kolmogorov Smirnov test (KS-test), t-test, and Wilcoxon signed-
rank test were used to arrange numerical results of the metadiscourse features. Another study on
metadiscourse was conducted by Herriman (2014) who studied metadiscourse features in non-fiction
texts across different languages and their translations. This study was corpus-based and used an
integrative approach and Hyland‟s (2005) model for data analysis focusing on content analysis using a
qualitative approach.
Translation Method and Metadiscourse
According to Newmark (1988), “translation is rendering the meaning of a text into another language
in the way that the author intended the text” (p. 5). The translator tries to closely interact with both
source and target texts of all kinds for particular purposes and particular recipients, usually in
response to a translation job commissioned by a client (Hatim & Mason, 2005). Williams (2005)
states that a translator requires the knowledge of literary and non-literary textual criticism since he has
to assess the quality of a text before he decides how to interpret and translate it. A translator translates
a source text into a target text, thereby implicitly or explicitly taking into account the form and genre
of the text and the fact that the whole process of translation is embedded in a cultural and political
context (Vermeer, 2007, p. 174). Translation of scientific texts, as happens with other texts of
specialization, can be approached from different perspectives e.g. discourse, register, genre,
terminology, etc. as suggested by the researchers (e.g. Gamero Pérez, 2001). One successful approach
is the pragmatic perspective that applies genre and register to translation (Jiménez, 2001). This allows
to identify all communicative functions and translates them into the target text.
Methodology
This study attempts to provide a platform for studying metadiscourse features across Punjabi (Figure
1) and Urdu languages (Figure 2). In this regard, a roadmap was devised to see that how these
features were mapped. For this purpose, both Punjabi and Urdu languages were dealt with separately,
the boosters as metadiscourse features were mapped across Punjabi and Urdu languages using
machine transliteration.
Figure 1. Mapping of Boosters in Punjabi Language
Figure 2. Mapping of Boosters in Urdu Language
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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211
Development of Boosters
A study by Siddique, Mahmood, and Iqbal (2018) has already developed a comprehensive list of
boosters considering two sources i.e. Hyland (2005) and the software (textinspector.com). This study
considered the taxonomy of boosters by modifying it according to the requirement (Table 1).
Table 1. List of Boosters (proposed in Siddique, Mahmood & Iqbal, 2018)
Sr.No.
Boosters
Sr. No.
Boosters
Sr.
No.
Boosters
Sr.
No.
Boosters
1
actually
21
demonstrated
41
indeed
61
show
2
always
22
demonstrates
42
indisputable
62
showed
3
apparent
23
determine
43
indisputably
63
shown
4
believe
24
doubt
44
it is clear
64
shows
5
believed
25
doubtless
45
know
65
sure
6
believes
26
essential
46
known
66
surely
7
beyond
27
establish
47
must
67
the fact that
8
beyond doubt
28
established
48
never
68
think
9
by far
29
even if
49
no doubt
69
thinks
10
certain
30
evident
50
obvious
70
thought
11
certain that
31
evidently
51
obviously
71
truly
12
certainly
32
find
52
of course
72
undeniable
13
certainty
33
finds
53
prove
73
undeniably
14
clear
34
found
54
proved
74
undisputedly
15
clearly
35
I believe
55
proves
75
undoubtedly
16
conclusively
36
in fact
56
realize
76
well known
17
decidedly
37
incontestable
57
realized
77
without doubt
18
definite
38
incontestably
58
realizes
78
won‟t
19
definitely
39
incontrovertible
59
really
79
true
20
demonstrate
40
incontrovertibly
60
should
The number of 79 boosters were considered for transliteration purposes across Punjabi and
Urdu languages. To transliterate the boosters across Punjabi and Urdu languages, the following
procedures were adopted.
Process of Transliteration
The taxonomy of boosters was transliterated into Punjabi and Urdu languages. The procedure of
transliteration of both Punjabi and Urdu languages was explained.
Punjabi Language
In the case of Punjabi transliteration, several steps were followed. Firstly, all boosters were
individually transliterated through software i.e. Akhar (2016). The steps of transliteration were
portrayed through pictograms in figures 3 to 5.
Step 1: All boosters were individually searched in the dictionary of Akhar (2016). As a result, the
transliteration was noted in the Gurmukhi script.
Figure 3. Finding Words in Gurmukhi via Dictionary (Akhar, 2016)
Step 2: After searching outcomes, the resultant occurrence in the form of Gurmukhi was pasted onto
the writing page and then Gurmukhi was transliterated into Shahmukhi (Figure 2).
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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212
Figure 4. Transliteration of the Searched Gurmukhi into Shahmukhi Words (Akhar, 2016)
Step 3: After the transliteration from Gurmukhi into Shahmukhi, for better a view, the transliterated
occurrence was brought to notepad for the further procedure (Figure 3).
Figure 5. Retrieving Transliterated Shahmukhi Words into Text-File (Akhar, 2016)
Means of Punjabi Words Retrieval
For having Punjabi translation, two sources were used i.e. Punjabi Corpus (Akhter, Mahmood &
Nadeem, 2019; Arslan, Mahmood & Hayat, 2019) and Akhar (2016). These sources helped seeking
boosters by providing examples.
Process of Identifying Punjabi Translations of Boosters
A procedural attempt, utilizing above discussed the sources, was made to have a Punjabi translation of
the boosters. After using the first source (Akhar, 2016), firstly a variety of Punjabi translations of the
same boosters was recorded. Secondly, the outcomes from machine transliteration (Akhar, 2016) of
boosters were refined after removing the transliterated Gurmukhi words which were autonomously
transliterated. Using Punjabi corpus, a list of boosters was studied and an expert finalized the presence
of transliterated boosters in Punjabi corpus. After using both sources for having Punjabi transliteration
of boosters, both transliterations were merged.
Process of Cleansing in Punjabi Transliteration
After transliteration of boosters in the Punjabi language, the obtained taxonomy of transliterated
boosters into Shahmukhi was cleaned. The process of cleaning revealed that the influence of
Ghurmukhi was observed and then cleaned in transliterated boosters in Shahmukhi script (Table 2).
Table 2. Differences Removed in Shahmukhi Punjabi Transliterated Words
Sr.
No.
English
Gramma
tical
Category
Source 1
Dictionary
(Akhar):
Shahmukhi
Differences
removed
(Gurmukhi)
Refined
Words
Source 2
Punjabi
Corpus
Merge:
(Refined
+Punjabi
Corpus)
1
Actually
Adverb
Table 2 revealed that the current study used two different sources (i.e. Akhar software, 2016)
dictionary and Punjabi Corpus) for extracting translations in the Punjabi language. To remove
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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213
differences, the irrelevant words as errors transliterated in Shahmukhi from Gurmukhi were manually
removed. After removing the differences, both sources (where the translations were taken) were
mapped together.
Process of Mapping Identified Boosters
After cleansing the transliterated errors, the next process of mapping was made through the following
steps. The purpose of this process was to observe and verifying the presence of transliterated Punjabi
boosters. For mapping's sake, the Punjabi translations of both sources were mapped together (Table
3).
Table 3. Mapping of Identified Boosters
Sr.
No.
Boosters
Grammatical
Category
Sources
Merge (Akhar+Punjabi
Corpus)
1
Actually
Adverb
Punjabi Corpus
Akhar
As mentioned in Table 3, the translations of the word “actually” were assisted by two
sources. The first source i.e. Punjabi corpus contributed to a single translation “. The second
source i.e. Akhar (2016), contributed to two translations of the same word “چس
and ”.
Finally, the word “actually” was transliterated into the Punjabi language and mapped to three
transliterations.
Urdu Language
The same processes were applied to translate boosters in the Urdu language. To transliterate boosters
in the Urdu language, several steps were followed. Firstly, both sources provided Urdu translations.
The step of transliteration was presented through a picture (Figure 6).
Step 1: A taxonomy of boosters was searched in dictionary: ijunoon. As a result, the transliteration
was noted.
Figure 6. Finding Translation of Words in Urdu via Dictionary: ijunoon
Step 2: After searching outcomes, the resultant occurrences were noted as translations of the words.
Means of Urdu Words Retrieval
For this purpose, the two sources were used to transliterate boosters in the Urdu language such as
Urdu Thesaurus and a dictionary: ijunoon. These sources helped in seeking boosters by providing
examples, in which boosters were used.
Process of Identifying Urdu Translations of Boosters
A procedural attempt was made to have an Urdu translation of the boosters. After using the first
source i.e. Urdu Thesaurus, firstly a variety of Urdu translations of the same boosters was recorded.
Secondly, the outcomes from machine transliteration (a dictionary: ijunoon) of boosters were refined
after removing the transliterated Urdu words that were autonomously transliterated. Using Urdu
corpus, a list of boosters was studied and the expert finalized the presence of transliterated features of
boosters in the Urdu corpus. After using both sources, for having Urdu transliteration of the feature of
boosters, both transliterations were merged.
Process of Cleansing in Urdu Transliteration
After the transliteration of boosters in the Urdu language, the obtained taxonomy of transliterated
boosters into Urdu was cleaned. The process of cleaning revealed that the influence of machine
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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214
translation was observed and then cleaned in transliterated features of boosters. For example, see
Table 4.
Table 4. Differences Removed in Urdu Transliterated Words
Sr.
No.
English
Grammatica
l Category
Source 1
Dictionary:
ijunoon
Difference
s removed
Refined
Words
Source 2
Urdu
Thesaurus
Merge:
(Dictionary
+Urdu
Thesaurus)
1
Actually
Adverb
-
Process of Mapping Identified Boosters
After the process of cleansing the transliterated errors, the next process of mapping was made through
the following steps. The purpose of this process was to observe and verifying the presence of
transliterated Urdu boosters. For mapping, the Urdu translations of both sources were mapped
together (Table 5).
Table 5. Distribution of Transliterated Urdu Words
Sr. No.
English
Grammatical Category
Sources
Urdu Words
1
Actually
Adverb
Urdu Thesaurus
ijunoon
As shown in Table 5, the translations of the word “actually” were assisted by two sources.
The first source i.e. Urdu Thesaurus, contributed to a single translation i.e. “. The second
source, i.e. a dictionary: ijunoon, contributed to two translations of the same word i.e. “” and
“
”. Finally, the word “actually” was transliterated into Urdu language and mapped to three
transliterations.
Results and Discussion
This study developed the list of boosters for having transliterations across Punjabi and Urdu
languages. Table 6 represents the details about how the boosters (68 in number) were transliterated in
Punjabi 268 wordlist. Out of 268, only 164 words were found in the Punjabi corpus and the remaining
were absent. Besides, the left wordlist was keenly observed and some repetitive words were removed
from that wordlist. Finally, 91 words were not found in the selected Punjabi corpus.
Table 6. Results of the Formation of Boosters with its Punjabi Transliteration
Number of
Boosters in
English
Transliterated
in Punjabi
Differences
removed
Punjabi
Words
Sentences formed
Left
Words
Repetition
removed
Unique
Left
Words
Punjabi
WordN
et
Online
Punjabi
Corpus
Expert
68
268
..
268
..
164
..
105
14
91
For having boosters in Punjabi translation, the comprehensive table has been given below. In
Table 7, which represents boosters in Punjabi translation, a category of boosters has been derived
from past research conducted (Siddique, Mahmood & Iqbal, 2018) and further modified. The very
next column is about the grammatical category of the list of words that are being identified. After
modifying and providing grammatical categories of the taxonomy, these features have been
transliterated through the machine as above-mentioned. The other column contains the differences
found that have been removed and then the next two columns are the resultant of two sources. The
last column merges the variety of identified boosters from two sources.
Table 7. Identification of Boosters across Punjabi Language
Sr.
No.
Boosters
Grammatical
Category
Dictionary
(Akhar):
Shahmukhi
Differences
removed
(Gurmukhi)
Refined
Words
Punjabi
Corpus
Merge:
(Refined
+Punjabi
Corpus)
1
Actually
Adverb
2
Always
Adverb
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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215
3
Apparent
Adjective
4
Certainly
Adverb
5
Certainty
Noun
6
Clearly
Adverb
7
Conclusivel
y
Adverb
8
Decidedly
Adverb
9
Definitely
Adverb
10
Demonstrate
verb
Table 8 represents the details about how the boosters (74 in number) were transliterated in
Punjabi 278 wordlist. Out of 278, 34 differences were removed as shown in Table 8. Out of 244, only
134 words were found in the Urdu corpus whereas the remaining were not found. Next, the sentences
were formed through 3 sources i.e. Urdu WordNet, Online Urdu Corpus, and Expert opinions. The
last thing was when the left wordlist was keenly observed; 10 repetitive words were removed from
that wordlist. Finally, 88 words were not found in the selected Punjabi corpus. These were unique
Urdu left words.
Table 8. Results of the Formation of Boosters with its Urdu Transliteration
Number of
Boosters
in English
Transliterat
ed in Urdu
Differences
removed
Urdu
Words
Sentences formed
Left
Words
Repetition
removed
Uniqu
e Left
Words
Urdu
Word
Net
Online
Urdu
Corpus
Expert
74
278
34
244
134
2
10
98
10
88
On the other side, the same procedures have been implemented on the Urdu language for
having its transliteration of booster‟s features. In Table 9, a category of boosters has been derived
from past research and further modified. The very next column is about the grammatical category of
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
__________________________________________________________________________________
216
the list of words that are being identified. After modifying and providing grammatical categories of
the taxonomy, these features have been transliterated through the machine as above-mentioned. The
other column is about the differences that have been removed and then the next two columns are the
resultant of two sources. The last column merges the variety of boosters identified from two different
sources.
Table 9. Identification of Boosters in Urdu Language
Sr.
No.
English
Grammatical
Category
Sources
Translatio
ns of
Sources
Differences
Removed
Urdu Words
1
Actually
Adverb
Urdu Thesaurus
ijunoon
2
always
Adverb
Urdu Thesaurus
ijunoon
This study has particularly studied boosters. For this purpose, 79 boosters have been analyzed
across Punjabi and Urdu languages. After analyzing these features, the identified boosters were
studied to check their appropriateness through the examples as derived from Punjabi and Urdu
corpora. An instance of the word „Actually‟ as transliterated in Urdu, the identified translations in
Urdu from different sources have been exemplified. These examples have been retrieved from three
sources i.e. Urdu WordNet as proposed by the University of Engineering and Technology and Urdu
Corpus, Online Urdu corpus, and expert opinions (Table 10).
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
__________________________________________________________________________________
217
Table 10. Verification of Identified Transliterated Words in Urdu Sentences
Sr.
No.
English
Grammatical
Category
Sources
Translations
of Sources
Differences
Removed
Urdu
Words
Urdu
WordNet
Left
Urdu
Words
1
Actually
Adverb
Urdu Thesaurus
ijunoon
Online Urdu
Corpus
2
always
Adverb
Urdu Thesaurus
ijunoon
Online Urdu
Corpus
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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218
3
apparent
Adjective
Urdu Thesaurus
ijunoon
4
Certainly
Adverb
Urdu Thesaurus
ijunoon
Expert
Opinion
5
certainty
Noun
Urdu
Thesaurus+ijun
oon
ijunnoon
6
clearly
Adverb
Urdu Thesaurus
ijunnoon
7
conclusiv
ely
Adverb
Urdu Thesaurus
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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219
ijunnoon
8
decidedl
y
Adverb
Urdu Thesaurus
ijunnoon
9
definitely
Adverb
Urdu Thesaurus
ijunnoon
10
demonstr
ate
verb
Urdu Thesaurus
ijunnoon
Similarly, the list of boosters as transliterated in Punjabi using different sources has been
exemplified. These examples have been retrieved from the Punjabi corpus (Table 11).
Table 11. Verification of Identified Transliterated Words in Punjabi through Sentences
Sr.
No.
Boosters
Sources
Merge
(Akhar+Punjabi
Corpus)
Sentence Example
Left Words
1
Actually
Punjabi Corpus
Akhar
2
always
Akhar
3
apparent
Punjabi Corpus
Identification of Boosters as Metadiscourse across Punjabi ……. Siddique, Ahmad & Mahmood
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Akhar
4
Certainly
Punjabi Corpus
Akhar
5
certainty
Punjabi Corpus
Akhar
6
clearly
Akhar
7
conclusively
Punjabi Corpus
Akhar
8
decidedly
Punjabi Corpus
Akhar
9
definitely
Punjabi Corpus
Akhar
10
demonstrate
Akhar
Conclusion
To sum up this study, boosters are lexical items that are used to create an intensity in the text and
enhance a writer‟s narrative significance. 79 boosters as metadiscourse features are acquired
(Siddique, Mahmood & Iqbal, 2018) and transliterated across Punjabi and Urdu languages. Through
the transliteration process, it is evident that boosters are pervasive across Punjabi and Urdu languages.
To find out the boosters across Punjabi and Urdu languages, the different ways such as translation
made through the software: Akhar (2016) and the acquired corpora of both Punjabi and Urdu
languages have been used in this study. In this way, the devised methodology including translation
processes for both languages (i.e. Akhar software, Punjabi corpus, Urdu thesaurus, and online
dictionary: ijunoon) helps explore other metadiscourse features across Punjabi and Urdu languages.
Finally, the explored transliterated boosters across Punjabi and Urdu languages are closer to the
boosters in English concerning their functions in such languages. In this way, Punjabi and Urdu
languages have more diversity of boosters in comparison with English language boosters.
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