English Learning Assistant Application with a Translation Approach
Using Rule Based System
Daniel M. D. U. Kasse, Patrisius Seran and Christa E. B. Bire
Politeknik Negeri Kupang, Penfui, Kupang, NTT, Indonesia
Keywords: English Learning, Dictionary, Rule Based, Translation.
Abstract: English has moved to improve its linguistic status, which is starting to act as a second language and
language
of instruction. This is often found in the social sphere, especially in youth, and education. The use
of English also has an impact on education and the economy. In the field of education, the availability of
sophisticated
translation tools online opens the way for students to translate a text more easily. However, in
real conditions, Indonesian students still find it difficult to practice their English skills. The purpose of this
research is to make
an application as a tool to learn how an English sentence can be translated into
Indonesian. This application not only displays the translation results but also displays the types of words,
sentence patterns to produce
English translations and materials.
1 INTRODUCTION
The use of English in Indonesia in general has a great
influence, although it is still a foreign language.
English has moved to improve its linguistic status,
namely starting to act as a second language and
language of instruction. This is often found in the
social sphere, especially youth, and education. The
use of English also has an impact on education and
the economy.
In the field of education, the availability of
sophisticated translation tools on-line opens the way
for students to translate a text more easily, media that
expose them to English such as programs on
television, music, commands on social media
applications and their gadgets. can increase their
knowledge. on how to understand English text and
convert information into Indonesian. However,
problems can also arise from tools and media that
help them understand English, such as if students
receive translations that do not match the true
meaning after they enter sentences in the source text,
without considering polysemy, transliteration, and
culture. the use of language, the idioms used and so
on, the result of the translation may not be accepted
because it does not convey the idea that the author of
the source text is trying to convey.
English teaching in Indonesia must be improved
if you want to get better results. Student needs
should be the focus of attention in teaching. The
success of teaching English depends on student
achievement in
terms of the goals that have been
determined before
the program starts. English
teachers must be open- minded and ready to keep
learning and strive for better teaching outcomes.
All the necessary information and knowledge must
be used to make
teaching English successful.
English teachers should
be able to choose teaching
materials such as books, journals, audio-video tape
recorders and cassettes, independent access and
computerized language
teaching to facilitate
language learning so that
students can achieve
effective language learning (Richards, 2001:230).
We need to be aware that
language teaching
methods can change over time as can fashion. But
we can always judge whether a
particular method
is suitable for our purposes. It is
important for us
to be open-minded and ready to try new methods to
improve the quality of teaching English. In real
conditions, Indonesian students still
find it
difficult to practice their English language
skills
in communicating. The purpose of this research is to
create an application that not only displays the
results of the translation but also how an English
sentence is translated into Indonesian.
Kasse, D., Seran, P. and Bire, C.
English Learning Assistant Application with a Translation Approach Using Rule Based System.
DOI: 10.5220/0012064600003575
In Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science (iCAST-ES 2022), pages 1079-1083
ISBN: 978-989-758-619-4; ISSN: 2975-8246
Copyright © 2023 by SCITEPRESS Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
1079
2
RULE BASED SYSTEM
Rule Based System (RBS) is an expert system that
uses rules to present knowledge. This RBS theory
uses a simple technique, starting with the basic rules
that contain all the knowledge of the problems
encountered which are then coded into if-then rules
containing data, statements and initial information.
The system will check all the if condition rules that
define the subset, conflict sets that exist. If found,
then the system will perform a then condition. This
loop will continue until one or two conditions are met,
if the rules are not found then the system must exit the
loop (terminate).
In the application of the Rule Based System in
the
process of translating sentences from English to
Indonesian, it is based on the rules of English
grammar. English has several sentence patterns,
namely:
Pattern 1: Simple Sentence
One independent clause (SV.). E xample:
Mr. Potato Head eats monkeys.
I refuse.
Pattern 2: Compound Sentence
Two or more independent clauses. Example:
Mr. Potato Head eats them for breakfast every
day, but I don’t see the attraction.
Pattern 3: Complex Sentence
One independent clause PLUS one or more
dependent clauses. Examples: He recommends
them highly because they taste like chicken
when they are hot.
Pattern 4: Compound-Complex Sentence
Two or more independent clauses PLUS one
or more dependent clauses. Example: Mr.
Potato Head said that he would share the secret
recipe; however, if he does, Mrs. Potato Head
will feed him to the piranhas, so we are both
safer and happier if I don’t eat monkeys
or steal recipes.
To be able to read input from the user, a
parsing
process with context free grammar is
used. Most
systems for modeling constituent
structures in
English or other natural languages are
using Context
Free Grammar or CFG.
Figure 1: Rules-based translator system.
For a Context Free Grammar has four
parameters (technically called 4-tuple)
N: A collection of non-terminal symbols (or
variables){NP, VP, PP}
: Terminal symbol set {det, noun, verb,..}
P: The production set, which is expressed in
the form A α where A is a non-terminal
symbol {<NP> det noun}
4. S: Start symbol
The parsing method used is top down. The step
is to
find all the appropriate grammar rules. In the
top- down parser there is a strategy called depth-
first
which looks for the appropriate grammar for
each of the first and subsequent entries.
3
RESULTS AND DISCUSSION
3.1 System Implementation
The translator system is implemented using four
modules that have different functions. Here are the
four modules along with a brief description.
3.1.1 Modul Indentifikasi
The initial stage is the preprocessing stage which is
carried out in this module. At the initial stage, a
checking process will be carried out on user input,
whether it is a word or not (in this case it is a phrase
or sentence). Input in the form of words will be
translated on the translator module while input in the
form of phrases or sentences will undergo a
preprocessing process. The preprocessing stage
includes changing abbreviations (contractions) such
as the word Ill to be changed to I will. In the
simple future tense, there is the use of tobe going to
which is
changed to will. The tokenization stage is
carried out to get tokens in the form of words
Rules Collection
English
sentence
System Result
Dictionary
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which are then converted into a single form such as
the word kicks which is converted into the word
kick. The next stage
is checking the words and
tenses. Input that meets the
criteria (in this case, all
words are in the word dictionary database and the
tenses used include
simple present tense and simple
future tense) will be
given to the parser module to
perform the scanning process (parsing). The initial
stage is the
preprocessing stage which is carried
out in this
module. At the initial stage, a checking
process will
be carried out on user input, whether it
is a word or not (in this case it is a phrase or
sentence). Input in
the form of words will be
translated on the translator
module while input in
the form of phrases or sentences will undergo a
preprocessing process. The preprocessing stage
includes changing abbreviations (contractions) such
as the word Ill to be changed to I will. In the
simple future tense, there is the use of tobe going
to which is changed to will. The
tokenization
stage is carried out to get tokens in the
form of
words which are then converted into a single
form
such as the word kicks which is converted into the
word kick. The next stage is checking the words
and tenses. Input that meets the criteria (in this case,
all words are in the word dictionary database and the
tenses used include simple present tense and simple
future tense) will be given to the parser module to
perform the scanning process (parsing).
3.1.2 Modul Parser
This module implements syntax rules in context free
grammar. The process for analyzing syntax rules is
called parsing. The parsing method used is top down
with a depth first strategy (top down depth first
parser). The parser will analyze the syntax structure
of the input provided by the user so that the structure
of the user input is obtained.
Table 1: Syntax rules.
Non terminal Terminal
<S> <NP> <VP>
<S> aux <NP> <VP>
<S> wh <NP> <VP>
<S> wh aux <NP>
<S> wh aux <NP> <VP>
<NP> det noun
<NP> pron
<VP> verb <NP>
<VP> verb inf <NP>
<VP> verb
The symbol to the left of the arrow is a non-
terminal
symbol and to the right of the arrow is a
terminal
symbol. Table 2 is a description of some of
the
symbols used.
Table 2: Symbol Description.
Simbol Arti
<S> Sentence
<NP> Noun Phrase
<VP> Verb Phrase
adj adjective
pron pronoun
aux auxiliary
det determinant
not negative word
noun noun
verb verb
wh wh-question
propnoun proper noun
inf to infinitive
Pada proses parsing, sistem akan melakukan
pencocokan seluruh aturan sintaks terhadap input
user. Berikut merupakan contoh dari proses parsing
(dengan konsep parsing tree) dalam context free
grammar.
Figure 2: Parsing tree.
From the results of the parsing process, the
input
structure from the user is pron verb det noun.
In the
parsing process there are several processes
English Learning Assistant Application with a Translation Approach Using Rule Based System
1081
including 'expand', 'match', and 'backtrack'. Expand
is the
process of replacing non-terminal symbols
into terminal symbols according to the existing
production rules in the syntax rules such as <NP> to
pron. Match
is the process of matching user input
word types with
syntax rules. Backtrack is the
process of going back to a non-terminal symbol
from a previous production.
3.1.3 Modul Translator
In this module, the MD-DM pattern rules are
implemented, namely the Explaining Explained word
pattern which is commonly found in English texts is
changed to the Explained - Explained word pattern
which is commonly found in Indonesian texts. An
example of the MD pattern is the big house. Table 3
shows the MD-DM pattern rules used.
Table 3: Aturan Pola MD-DM.
No. JK1 JK2 JK_1 JK_2
1 Aux Not Not Aux
2 Adj Noun Noun Adj
3 Det Noun Noun Det
4 Propnoun Noun Noun Propnoun
5 Noun Noun Noun Noun
For user input in the form of word units, the
translation will be carried out directly without going
through these stages. The results of this module are in
the form of word tokens in Indonesian.
3.1.4 Modul Materi
At this stage, the system will display the material
according to the type of words obtained from the
identification.
3.2 System Testing
In the process of testing the system with a black box
can be determined by studying the input and output.
In this test, the focus will be on testing from the
original language (English) to the target language
(Balinese) whether it is in accordance with the
expected results based on the system design and the
suitability of the system interface. Table 4 is some of
the data used in testing the system using the black box
method.
Table 4: Black Box Method Test Data.
No
Data
Sample
Keterangan Task Status
1 I Love
You
Correct
input
(simple
sentence
pattern)
Process
and
display the
translation
results in
Indonesian
OK
2
I was
happy
Correct
input
(simple
sentence
pattern)
Process
and
display the
translation
results in
Indonesian
OK
3
My elder
brother
became
an
engineer
in
1988
Input that
has
a
complex
sentence
pattern
Processes
and
displays a
warning
that Input
has a
complex
sentence
pattern
OK
4
was happy
I
Input that
has
an
unrecognized
pattern
Processes
and
displays a
warning
that the
Input has
pattern not
recognized
OK
4
CONCLUSION
From the implementation of the concept of translating
English text to Indonesian text using the Rule Based
method as well as from the results of translation
testing as above, several conclusions can be drawn,
namely:
This English to Indonesian text translator can
translate sentences in
"simple sentence
pattern" quite well.
This English to Indonesian text
translator is
able to recognize the types
of words in the
entered sentence.
This research is still in progress so it is
not
yet fully completed
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