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<small>NATIONAL ECONOMICS UNIVERSITYFACULTY OF FOREIGN LANGUAGESDEPARTMENT OF BUSINESS ENGLISH</small>

NGUYEN THU TRANG

PERCEPTION OF UTILIZING TFLAT DICTIONARY APPLICATIONIN TRANSLATION AMONG BUSINESS ENGLISH STUDENTS,

INTAKE 61

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NATIONAL ECONOMICS UNIVERSITY

<small>FACULTY OF FOREIGN LANGUAGESDEPARTMENT OF BUSINESS ENGLISH</small>

NGUYEN THU TRANG

PERCEPTION OF UTILIZING TFLAT DICTIONARY APPLICATIONIN TRANSLATION AMONG BUSINESS ENGLISH STUDENTS,

INTAKE 61

Hanoi, 11/2022

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The success of this research required the help of various individuals,without them, I would not have met the objectives of this study. I want to expressmy gratitude to the following people for their significant help and support.

First and foremost, I would like to express my deep and sincere gratitudeto the advisor, M. Le Thu Huong, National Economics University, for providinginvaluable guidance throughout this research. Her patience, dynamism, andsincerity have deeply inspired and motivated me throughout the work. It was a

privilege and honor to work and study under her guidance.

My special thanks are for 79 BE students from the intake 61 in the NEUfor their cooperation in answering the questionnaire. Their honest and

informative answers are crucial to help me continue this study.

Last but not least, I am grateful to my parents for their love, care, andsacrifice for always staying by my side and having my back in anycircumstances. I also would like to thank my friends for their understanding and

continuing support so that I can accomplish this research work.

I have tried to gather all relevant documents regarding this subject. Theremay be shortcomings, factual errors, and mistaken opinions, which I amresponsible for, but I will try to give a better volume in the future.

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The TFlat dictionary application is employed frequently by senior studentsin the Faculty of Foreign Language at National Economics University, as shownin this study. Students majoring in Business English use this tool to improve their

efficiency and productivity in translation tasks. The research is based on data

supplied by a survey of 79 students intake of 61 from the faculty.

The present study is an attempt to discover BE senior students’

perspective and habits of exploiting TFlat dictionary app in translation. Firstly,

the findings show that the participants held positive attitudes toward the use of

this tool. Therefore, students make use of the app frequently, though the figuresfor each feature vary according to users’ purpose.

Secondly, the research uncovers the advantages and drawbacks of TFlat insupporting the translation process. Considering the features the app provides, thistool is often used during the first stage of the translation process for mostprofessional and administrative materials. Not many students utilize the texttranslation feature to translate documents compared to the use of the dictionaryfunction. Though a majority of participants agree that students should make useof TFlat to broaden their vocabulary range, the usage percentage for featuresrelating to vocabulary is not significant.

Finally, the study points out that most BE students find TFlat dictionaryapplication helpful and recommend others to use it. In terms of translation, usingthis tool will save much time for students and make the work easier. Aside fromsignificant help in the translation process, the app serves as a pocket diary ofvocabulary that can be opened anytime and anywhere. Therefore, it is proposedteachers should recommend the app to their students so that they can accomplishtheir translation tasks satisfactorily. Moreover, it is imperative that teachers guidestudents to employ the app in an effective and proactive way to avoid

Further research might investigate the popularity of TFlat dictionaries intranslation compared to other tools or the effectiveness of TFlat use in translationamong students from other majors.

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LIST OF ABBREVIATION

AI: Artificial Intelligence

Apps : Applications

BE: Business English

HMT : Hybrid Machine Translation

IELTS: International English Language Testing System

MLD : Monolingual Learner's DictionaryMT : Machine Translation

NEU : National Economics University

NM__ : Neural Machine Translation

RBMT: Rule-Based Machine Translation

SMT_: Statistical Machine Translation

SL : Source Language

TOEFL: Test of English as a Foreign Language

TOEIC: Test of English for International Communication

TL : Target Language

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TABLE OF FIGURES

Figure 1: Percentage of BE students who know about TFlat App ... 17Figure 2: Channels from which BE students know about TRFlat... 18

Figure 3: Students’ opinion on effectiveness of each TFlat feature ... 19

Figure 4: Students’ frequency of using TFlat application in translating practice 20Figure 5: Frequency of using the text translation for different types of translation

Figure 6: Translation steps in which students use the text translation in TFlat ...22Figure 7: Frequency of using TFlat to improve translation skills and performance

¬—... 23

Figure 8: TFlat’s advantages over other translation apps/ programs... 24

Figure 9: Common problems students face when using TFlat to translate... 26Figure 10: Helpful tips to improve BE’s translation by using TFlat application .27Figure 11: BE students’ overall perspective of TFlat app...ceesccessceesteeeeees 29

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TABLE OF CONTENT

ABSTTRACTT,...- 0G 9 HH nọ TH nh 1

LIST OF ABBREVIATTION...- - -- LH 1S TT il

TABLE OF FIGURES...-- - G1 ST tt 11CHAPTER 1: INTRODUCTION...-- 2Á SH * SH ng Hưy 1

1.1. Background ^....43:-ư:ưƯ-+-›ƠƠƠƠƠ-Ơ 11.2. Rafionale... - - - - ng HH no kh 2I9)... ....a.aậăă... 2

2.1.3.1. Literary [YAHSÏQfÏOHH...Ă Ăn T11 khen rưy 7

2.1.3.2. Professional †rA'LSÏ4fÏOlH... cv nhe rưy 7

2.1.3.3. Technical translation ... «cà vn tk re 72.1.3.4. Administrative fFAHSÌQHÏOPH... vn vn ve, 82.2. Machine translation ... ...- - - -- HH HT HH HH, 82.2.1. Overview of machine translation (MT) ... <5 ssssseeeereses 82.2.1.1. Definition of machine translation ...ccccccccceecsceesseetenseeteneeteneees 82.2.1.2 Advantages Of ÌMÍTÌ... . -- - c 11v vn ve rry 82.2.1.3. Problems with ÌMÍTT... - -- -c c cv ve rry 9VÝJyÀ)221J8.0 0 ... 102.2.2.1. Statistical Machine Translation (SMTT))...- << «<< << «+ s++++e+s 102.2.2.2. Rule-Based Machine Translation (Đ.BÌMTT)... << << ++++++++ II2.2.2.3. Hybrid Machine Translation (HMT) ...ccsssss*ss+++++*sss 112.2.2.4. Neural Machine Translation (ÌNÌMTT))... s55 5s s« << «<< ssssssssss 11

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P0 0i) 0n... hố... 12

2.3.1. Definition of online đỉCÍÍOH(IFW...ẳ. ST xe ren 122.3.2. Types Of đỈCÍÍOHŒTHGS... Gv HH KH 122.4. Overview of TFlat dictionary application...--- se 13

CHAPTER 3. FINDINGS AND DISCUSSION...ii 173.1. BE students’ attitudes towards using TFlat in translation practice....173.2. Frequency of using TF lat in translation practice of BE students intake

3.3. Possible methods to improve translation performance by using TFlat

¬—... . ... 24

CHAPTER 4. CONCLUSION... HH HH nh HH Hy 304.1. SummarF... Gà n kcrh 300)... 1n... ... 30

4.3. Suggestions for further research...- - --- cc s3 tveeirreeserree 31

REFERENCESAPPENDIX

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Among myriad languages in the world, English has managed to becomethe global language or lingua franca. There are about 350 million native English

speakers, while over 430 million speak English as a second language. Most

students around the world learn English at school as a compulsory subject, andmore and more countries consider adopting English as their official language.The essential function of this lingua franca can be observed most clearly in thebusiness environment. Because no country could stay outside the global tradingnetwork, English has become a crucial factor to connect and interact withbusiness partners from other countries. As a result, more and more people investtheir time and money to improve their English with the hope of a brighter future.

When mentioning fields relating to languages, translation is one of the

most common tasks. This is a job requiring a set of advanced skills. A translatorneeds to have a comprehensive understanding of various aspects, along with theability to master both English and their native language. However, in this day andage, translating has become significantly easier thanks to the advent of moderntechnology. Translators could take advantage of translating tools such as CAT,machine translation, and online dictionaries to improve their performance. Inaddition, they have more chances to immerse themselves in a foreign language inthis global era, so their learning process would probably be less challenging.

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1.2. Rationale

There are different choices for an amateur translator when it comes tomachine translation. An undergraduate majoring in translation can easily accesswebsites such as Google translate and Microsoft translate to finish theirassignment. Along with websites, many applications are created to be moreconvenient for translators. There are various features on the applications such asuploading photos, taking pictures, or using the microphone to input the sourcetexts. After a simple click and a few seconds, the translated version will appearon the screen. Though these translated texts are not perfect, the translator couldsave much time by editing them instead of doing every step of translation in thebeginning.

With the purpose of helping English students take advantage of

technology in translating practice, this research analyses how students currentlyutilize translation applications to develop their skills and make their work better.The study focuses on the Tflat dictionary application, a familiar app forVietnamese students, including those not majoring in the English language. This

app is known as an English-Vietnamese-English dictionary, so not many people

notice its translating function. As both dictionary and machine translation areessential to translators’ jobs, the author believes this app would help students alot in their assignments. Furthermore, the app includes a feature allowing users to

learn and revise vocabulary, which is helpful for translators’ learning process.

The research will be conducted with the participation of the students of intake 61of the Faculty of Foreign Language at the National Economics University, Hanoi,

Vietnam. Specifically, the study will find out and analyze “Perception of utilizing

TFlat application in translation among Business English students, NEU, intake61”.

1.3. Objectives

The research aims:

e To investigate BE students’ perception of the TFlat application.

<small>e To evaluate the TFlat application in supporting the translation process</small>

based on actual students’ utility.

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e To propose possible methods to help BE students improve their translationperformance by utilizing the TFlat app.

1.4. Research questions

In order to achieve the research aims and objectives, the study is to find out theanswers to the following research questions:

e@ What are the BE K61 students’ attitudes towards TFlat application?

e How the BE KóI students apply Tflat for translating?

e What are possible ways of utilize TFlat to improve translation skills and

performance according to BE K61 students?

1.5. Research scope

The main research subjects of this study are BE students, intake 61, at NEU.

Time scope: from September to November 2022.

Based on the collected datas, comparisons and analysis are carried out todelve deeper into the situation of using the app for translation among BE students

intake 61.

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CHAPTER 2: LITERATURE REVIEW

2.1. Translation

2.1.1. Translation definition

There has been a myriad of translation definitions that are elucidated by

linguists around the world. The eminent American linguist Eugene Albert Nidaalso admitted the diversity of translation understanding. This variety isunderstandable because the definitions mostly depend on the translated materials,the purpose of the publication, and the prospective audience’s needs.

However, a general definition separate from the mere transference ofmeaning is postulated by E. Nida and C. Taber (1969: 12). He sees translation asa reproduction in the “receptor language” that ensure the “closest natural

equivalent” of the SL in terms of both meaning and style.

Roger Thomas Bell (1991: 56), the author of the book “Translation and

Translating: Theory and Practice” shares the same view as the two linguistsabove. Being a professor of linguistics, he considers translation as a replacementof a language by the representation of another language, equivalent in both

semantic and stylistic aspects.

The emphasis on “equivalence” is also found in the following concepts oftranslation, given by Meetham and Hudson (1972) and Catford (1965):

“Translation is the replacement of a text in one language by a replacement of anequivalent text in a second language. ” (Meetham and Hudson, 1972: 713)

<small>“Translation is the replacement of textual material in one language (SL) by</small>equivalent textual material in another language (TL).” (Catford, 1965: 20)

Koller refered translation as “the result of a text-processing activity” , andthe relationship between the target language text and the source language text isdesignated as equivalence relation (1995: 196).

Christiane Nord (2007: 141), however, defines translation according totwo senses: wide and narrow:

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<small>“Translation is, in a narrow sense, any translational action where a source textis transferred into a target culture and language. According to the form andpresentation of the source text and the collectibility of the target text we distinguishbetween oral translation ( ‘interpreting’ ) and written translation (‘translation’ in the</small>

<small>narrow sense).””</small>

Nonetheless, Barzegar (2008) only uses the term “translation” to refer to

the replacement of a written message in one language with an equivalent message

in another language.

Among the above definitions, Nida and Taber’s theory seems to be the

most fundamental concept of translation. The basic idea of the translation processis the production of a TL product as coherent and accurate as the SL text in termsof semantics, grammar, and style. This means that apart from accurate

transference in meaning, the translator should pay attention to syntax and dictionin the TL. The translator needs to adjust the vocabulary and structures in the

texts, meaning that they have to deal with multiple complex tasks to ensure acomprehensive TL version.

2.1.2. Translation process

Similar to the concept of translation, the process of translating a documentis different from one person’s view to another. While some divide this activity

into three main phases, others separate the process into smaller parts.

According to Gouadec, translation is a series of activities including three

phases: pre-translation, translation, and post-translation. Pre-translation involves

anything happening before the translator receives the document. Some activitiesincluded in this phase may be working with the publisher or the document’sauthor. Translation involves the translator’s efforts to transfer the text’s contentfrom the source language to the target language. The translator need to ensure theaccuracy in both document’s content and language style. The final phase, post-translation, phase involves activities after the delivery of the translated version.

This study concentrates on the second and main phase of the entireprocess — translation. The translation phase covers three stages: Pre-transfer,transfer, and post-transfer. These three activities are also known under the names

of pre-drafting, drafting, and post-drafting respectively.

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Pre-drafting covers all preparation before the actual translating task, suchas pre-reading the material and searching for the terminology to understandkeywords and terms in the source text. The translator needs to comprehend the

document in terms of content, background, and language. After obtaining ageneral idea of the source text, a list of equivalent terms in the target language

should be prepared to make the next stage easier and quicker.

Drafting is the second task in the translation process. This is the main partin which the translator uses their knowledge and skills to transfer the material tothe target text. The translator must ensure semantic accuracy, grammaticalcorrection, and appropriate style in the TL. This used to be the most painstakingtask a translator has to deal with. Despite thorough preparation, it is challengingto translate a document in a short time while still ensuring the translation quality,especially for unfamiliar topics. Even when the terminology might be handledeasily, the translator needs to check the grammar carefully so that the translationis straightforward but accurate. Language style is another important aspect thatmust be noticed while translating. An inappropriate tone may lead tomisunderstanding and reduce the quality of the translation. Nevertheless, this stepis less demanding with the advent of modern technology and artificialintelligence. For less complicated materials, drafting is often taken charge of bymachine translation instead of humans now.

The final work of translation is the revision of the translated material,

which is called post-drafting. This is related to editing, proofreading, andcorrecting all the mistakes in the text to meet the quality demanded. At the time,this has become the most important stage of the translation process. Thoughmachine translation does much help for translators, its ability is limited. Forcomplex language phenomena such as metaphor, AI is unable to understand andtranslate properly into another language. Even a sentence with a strange ordifficult structure is hard for MT to handle. Thus, this stage is often done by

human translators, who would check the MT’s work and make necessary changes

to ensure accuracy and readability.

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2.1.3. Types of translation

Translation can be categorized into four main types based on subject area:literary translation, professional translation, technical translation, andadministrative translation.

2.1.3.1. Literary translation

Translated materials relating to literary works such as stories, poems, and

plays belong to this type. Literary translation is considered the most challengingtype due to the comprehensive knowledge it requires. Most of the words andexpressions in the literature contain multiple meanings. Therefore, the translator

needs to understand the words’ meanings, context, sound, and feeling behind the

terms. This means an extensive knowledge and experience of the culture of both

languages is necessary to translate humor, puns, and other similar elements of awork.

This type is challenging for translators also because in some cases, nosuitable translations could be found. A valid example is the translation of poetry.While the words in the SL are rhyming and form puns at the same time, it is

almost impossible to ensure both elements in the TL.

2.1.3.2. Professional translation

Another type of translation is professional translation, which includesprofessional documents such as in medical and legal fields. The purpose of thistype is to generate accurate information from the original materials. Withoutwordplay as a literary translation, documents of this type are easier for

Professional translation often contains numerous jargon regarding aspecific field such as medicine or law. Therefore, translators who take charge ofthe documents often are specialists in the area to ensure accuracy.

2.1.3.3. Technical translation

As the name may suggest, technical translations cover documents withtechnical contents such as engineering documents, instruction manuals, userguides, and technical training.

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Technical materials often contain complicated details, which require the

translator to have knowledge and experience with the industry to understand

completely. Additionally, formatting requirements and images may need to bechanged in some cases to ensure the reader knows what they should do

2.2. Machine translation

2.2.1. Overview of machine translation (MT)

2.2.1.1. Definition of machine translation

In Conformal Prediction for Reliable Machine Learning, 2014,

Shen-Shyang Ho defines machine translation (MT) as “an instrument to save time for

human translators”. MT is the application of artificial intelligence (AI) to

transfer material from one language (SL) to another (TL). This automated

process of translation has been an elusive problem for linguists and researcherssince the appearance of electronic digital computers. After decades of studying,MT now is widely used by both professional and amateur translators in variousfields. Most people minimize the time for translating by utilizing MT in the first

stage of translation before editing the work by themselves. Some familiarmachine translation tools are Google Translate, Microsoft Translator, andAmazon Translate.

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One of the apparent advantages of MT is the speed and volume. MT onlyneeds a few seconds to translate millions of words, and the content is better afterbeing used multiple times. For large-quantity projects, the organization can usecontent management systems along with MT to retain context when the content istranslated into different languages.

The second strength of MT is the enormous number of languages it

provides. While most human translators are only capable of translating from onelanguage to one or two others, MT offers translation in 50-100 languages ormore. That means users could translate materials across multiple languages in a

short time.

Another advantage of MT is the affordable cost and faster turnaround.Translation is a challenging task requiring a high level of various skills, sohuman translating service is expensive. With the ability to translate a largevolume of documents into multiple languages in a short time, MT help cut costand time to generate translation. Generally, MT takes charge of the initialtranslating stage by delivering basic translation. This version will be refined andedited by the human translation to ensure content equivalence and properlocalization.

Finally, MT could be integrated automatically into translation workflows.Many translation management systems rely on MT to automatically run atranslation before sending that to the human translator. This integration issuitable for the translation of internal documentation and communication, savingmuch time and cost for the system.

2.2.1.3. Problems with MT

Until now, machine translation only covers the fundamental phase in thetranslation process due to some issues. Even though neural MT, the mostdeveloped type, is able to learn through repeated use, it is unlikely to catch upwith human translators in the near future.

The most obvious drawback of MT is word-sense disambiguation. Thishappens when a word has more than one meaning, and the translator needs tounderstand and find the most suitable word in the TL. Yehoshua Bar-Hillelfigured this problem out in the 1950s. He claimed that a machine could never

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distinguish varied meanings of a word without a “universal encyclopedia”.

Scientists have been striving to deal with this challenge, and two approaches are

designed. The first one, “shallow approaches”, guesses the word’s meaning byapplying statistical methods to surrounding words instead of involving theknowledge of the text. The other is the “deep approach”, which requires insightresearch on the text to find out the exact meaning of the ambiguous words. Thedegree of AI currently is unable to access the “deep approach’, while the

successful “shallow approach’ is not effective due to the high chance of guessing

In addition, MT struggles to translate non-standard language. Unlike thestandard form of a language that is based on to develop Statistical-based MT andRule-based MT, non-standard language is not included. This means materials ofdialect or casual language are unlikely translated accurately into colloquial

One of the major issues with MT is named entities, which are concrete orabstract entities in the world with a proper name. If these entities are notidentified, they may be translated as common nouns, leading to misunderstandingor weakening the text's readability. There are some approaches to fix thisproblem. Transliteration is a possible choice, which finds the most corresponding

letters in the TL to replace the name in the SL. Nevertheless, this could damage

the translation’s quality. Another potential method is to use a “do-not-translate”list. To form this list, named entities still need to be identified in the first place.The final approach is applying a class-based model. Named entities will bereplaced with a token showing their “class”, such as “person name” or“geographical name”.

2.2.2. Types of MT

There are four main types of machine translation: Statistical MachineTranslation (SMT), Rule-Based Machine Translation (RBMT), Hybrid MachineTranslation (HMT), and Neural Machine Translation (NMT).

2.2.2.1. Statistical Machine Translation (SMT)

In 1947, Warren Weaver came up with the first concept of Statistical

Machine Translation. He believed that similar to logical-mathematical problems,

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languages had a clear logic. Therefore, the logical deduction could be applied to

transfer a text in SL to the equivalence in TL. This hypothesis became real with

the advent of powerful technology.

SMT can be understood as a tool for creating translations based onstatistical models whose parameters are derived from bilingual text analysis. Thistype of MT is only suitable for basic materials since it doesn’t take context into

2.2.2.2. Rule-Based Machine Translation (RBMT)

As the name refers, this type of Machine Translation generates translationbased on grammatical rules. In other words, RBMT will analyze the source and

objective language grammatically to translate the documents.

Due to the significant reliance on dictionaries, the RBMT needs a longperiod of time to attain proficiency. Therefore, the translated materials requirebroad editing from human translators.

2.2.2.3. Hybrid Machine Translation (HMT)

Hybrid Machine Translation, as the term indicates, contains characteristics

of both RBMT and SMT. HMT uses a translation memory, allowing it toimprove the translation’s quality substantially. Nonetheless, it is not perfect, andone of the biggest drawbacks is the need for post-editing from humans.

2.2.2.4. Neural Machine Translation (NMT)

The Neural Machine Translation model is designed on the basis of the

neural networks in the human brain, using artificial intelligence to improve itself.

After training, NMT can learn to perform more accurately in a shorter period oftime. There is no difficulty in adding more languages to this system. Google

Translate was the first engine to apply NMT for the purpose of translation.Because of the ability to self-develop through repeated use, NMT has becomemore and more popular around the world. This model is now the primarydevelopment of many tech giants.

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2.3. Online dictionary

2.3.1. Definition of online dictionary

An online dictionary is a dictionary created on the Internet, and users can

access it through a web browser. Some digital dictionaries are free, while othersmay require a fee to have access to extended content. Many online dictionariesare digitized from their print versions. Each dictionary website has its own designand features. Some of them are arranged as lists of words, and others mayprovide search tools, reverse lookups, and other features. A big advantage of

online dictionaries is the capacity to cover an enormous amount of topics,

ranging from technology, finance, and science, to other common fields. Another

benefit of this digital tool is that it allows users to bring it anywhere and use itanytime they want. Most traditional dictionaries are large and heavy, which

likely discourages learners from using them in some particular circumstances. In

contrast, online dictionaries are available and accessible as long as the learnershave a smartphone in their pockets. This kind of dictionary with its superiorconvenience and performance reduces much time for learners. Therefore, theonline dictionary has become ubiquitous in modern society and graduallyreplaced the paper version.

2.3.2. Types of dictionaries

There are many types of online dictionaries depending on the criteria usedto divide. As this research concerns the utility of dictionaries for the purpose oftranslating, only two types of digital dictionaries will be mentioned: The

bilingual dictionary and the monolingual learner’s dictionary.

A bilingual dictionary, also known as a translation dictionary, is aspecialized dictionary designed to translate words or terms from one language toanother. This type can be unidirectional, meaning that it only includes themeaning of one language, or bidirectional, which allows users to translate to andfrom both languages.

Additionally, a bilingual dictionary often provides the part of speech, verbtype, gender, and even pronunciation to help a non-native speaker comprehendthe word. Some dictionaries also indicate examples, usage, and related terms.

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In contrast to the bilingual dictionary, a monolingual dictionary defines

words and phrases in the native language. However, a monolingual learner's

dictionary (MLD) is designed to support people learning a foreign language. Thecommon premise that language learners should get used to the target languagethrough frequent exposure to it is a foundation of MLDs. Many believe that amonolingual dictionary is more helpful in improving learners’ proficiency intheir target language. Generally, MLD is more detailed and clearer than bilingualdictionaries. It includes information on grammar, usage, common errors,collocation, and pragmatics, which is overlooked by many standard dictionaries.Even native speakers barely notice these aspects as they tend to learn them

intuitively. As MLD is designed for language learners, the language it uses is

simple and straightforward. Despite such an accessible defining vocabulary,users need to have a firm foundation for the target language to fully understand

all the listed characteristics of a term in MLD.

2.4. Overview of TFlat dictionary application

TFLAT is a well-known Vietnamese dictionary and text translation utilitythat can be used for free and offline on mobile devices.

In addition to translating words and texts, TFLAT offers various usefulfeatures to help users improve their overall English ability. Eight noticeablefeatures of this application are described below:

English- Vietnamese dictionary

The application allows users to look up English - Vietnamese words with

standard and clear transliteration. Information is categorized into 7 pages:

- English-Vietnamese: showing the corresponding Vietnamese word withthe example

- Grammar: showing other structures of the word as well as words that areclose to the sound and meaning

- British English: explaining the meaning of words in English withexamples (only for particular words)

- Technical: listing the specialized meanings of the word

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- Synonyms: listing synonyms and antonyms for the word

- Image: showing an image that illustrates the meaning of the word (only

for VIP accounts)

- Note: you can make more notes here

Vietnamese-English dictionary

Unlike the English-Vietnamese dictionary, TFlat does not provide muchinformation around the Vietnamese word. Only the corresponding English wordand some examples are offered. However, users can write down their ownexamples or ways of use in the “note” function.

Quick lookup window

By selecting this item, an application window will be displayed on the

screen so that users can quickly look up a word while using another application.

This feature is very useful in some cases. For example, when reading anEnglish newspaper, if the user does not understand a word, they can click on the

application icon and then look up the word. For some phones, to use the above

feature, you must allow the TFlat application to be displayed on top of anotherapplication. However, this function is not active in the iOS operating system.

Text translation

Network connection is necessary to be able to use this feature. Users cantranslate both English sentences into Vietnamese and vice versa. In addition tothe normal keyboard input method, they can also record or capture text in real

Your words

When a user uses this feature for the first time, the TFlat application willask them if they want to log in. The purpose of logging in is for TFlat to save thedata in this section on TFlat's server. When the user changes their device orreinstalls the software, they just need to log back into the correct account to beable to recover the words they saved before.

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Google or Facebook accounts could be used to log in faster. However,

users are not required to log in to be able to use this feature.

In the free version, users can use only two folders in this section: “savedwords” and “words to learn”. The words can be moved from one folder to

another whenever the users want. There are four functions helping people learn

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their words, including “review”, “writing”, “game” and “game VIP”. Only VIPmembers can get access to the final one. Users can turn on the reminder on theapp if they want to set goals to learn new words every day.

Recent words

In this item, the application will display a list containing all the words that

users have looked up since installing TFlat.

Common Vocabulary

The TFlat app has vocabulary lists dedicated to a specific purpose.However, the content is not as good as the VIP vocabulary packages. Currently,TFlat offers the following five vocabulary lists:

- Irregular verbs

- TOEIC Vocabulary- IELTS Vocabulary- TOEFL Vocabulary

- 3000 Oxford Vocabulary

VIP vocabulary packs

This feature includes two items, “VIP Vocabulary Pack for Exam

Preparation” and “Textbook VIP Vocabulary Pack”. Users have to spend moneyto buy to be able to use these two.

The vocabulary packages in these two categories are carefully selectedand compiled by the TFlat developer. Therefore, the content will be better thanthe vocabulary lists in the "Common vocabulary" section. Vocabulary in this

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