Language Translation App
Team members:
1. B. Sirisha (21991A0564)
2. B. Aishwarya (21991A0594)
3. Y. Pawan Kumar (21991A0573)
4. B. Sandeep (21991A0593)
5. P. Mahesh (22995A0512)
6. M. Ravi Teja (22995A0513)
Project Guide:
Mr. G. Venkateshwarao(Assistant Professor dept of CSE(AI & ML))
Project Review Team:
1. Mr. M. Uma Maheshwarao (HOD and Assistant Professor dept of CSE)
2. Mr. G. Venkateshwarao (Assistant Professor dept of CSE(AI & ML))
3. Mrs. A. Krishnaveni (HOD and Assistant Professor dept of CSE(AI & ML))
4. Mr. M. John Timothy (Assistant Professor dept of CSE)
5. Mr. B. Rajasekharam (Assistant Professor dept of CSE)
ABSTRACT
In today’s globally connected society, the mutual understanding, cooperation, and
exchange to each other completely dependent on effective communication.
However, the vast diversity of languages is spoken worldwide. So, linguistic
differences frequently emerge as dangerous barriers, upcoming seamless
communication and constraining opportunities for meaningful interaction. Due to
these obstacles not only delay the development of interpersonal relationships but
also the possibility of global collaboration. So, the Real-Time language translation
app is a solution for addressing the frequently found problems of language barriers
in global communication. This app, which connects linguistic gaps in
communication between individuals and organizations, this is based on state-of-
the-art language processing technologies. This app provides instant and accurate
translations for conversations, documents and various forms of communication by
using Artificial Intelligence and Natural Language Processing to translate spoken
and written text in real-time. In this project we will be using NLP for tokenization,
text representation and neural machine translation. Deep learning frame works for
training neural networks which provide flexibility and speed. Flask or Django is
used to integrate the trained model into the API to perform translation tasks.
React.js to enable text input, language selection and translation display. By
combining all these advanced AI capabilities with user friendly interface, and real-
time translation the language translation app saves the time and strives to make
global communication easier and more accessible for everyone.
KEYWORDS: Language, Translation, communication, ML, DL, NLP, Neural
Machine Translation.
Introduction
Language Translation is the process for converting a written source language text
clearly, completely, accurately, and appropriately to a target language, Translation
allows information to be transferred across all the languages, expending the
accessibility for the information. Translation is a very hard and complex act that
always requires very close reading of a text in the source language, understanding
its meaning, context, and creating an equivalent and same text in the target
language .Today, translation is spread over widely and also accessible than ever
before.
A Language Translator app is a tool for translation, which helps people survive in
places even they are not familiar with those language. They can easily input their
message by giving the text as input or by speech as input and can translate it easily
into any other language. This also helps the people who are having difficulty in
writing with the help of speech recognition features. The text in an image can be
captured with a lens and it can be translated or converted into any language as per
the user's choice
PROBLEM STATEMENT
Communicating with the people becoming hard, when the user doesn't understand
the language spoken by the other user. By using this app, the user can easily
understand what he/she is speaking and translating it to the user who uses the app.
This app is very much useful for the people who travels from country to country or
from state to state i.e. the person who travels the world. Thia app increases the
business growth by communicating with all other countries and the people living
there. Moreover, it can recognize the text in an image exactly and translate it to the
language as per the user’s choice which reduces all the efforts for the user in the
typing of the text present. This app translates the image into the language.
Literature Survey
The experiences gained from a study carried out at the Hannover Medical School
regarding the use of a mobile translation application in hospital wards. The
conditions for successfully integrating these technologies in the care process are
discussed.[1]
We conducted a pilot study to evaluate the quality of a mobile language translation
app (iTranslate) with a voice recognition feature for translating diabetes patient
education material.[2]
An android mobile App for real-time bilateral Arabic sign language translation.
The system is designed to operate on isolated sign language words.[3]
Machine Translation Systems are part of Natural Language Processing (NLP) that
makes communication possible among people using their own native language
through computer and smart media devices. This paper describes recent progress in
language dictionaries and machine translation[4]
The Real-Time Language Translation App represents a paradigm shift in
overcoming language barriers and promoting global communication. The
application facilitates seamless communication between users across language
barriers [5]
This study aimed to evaluate iPad-compatible language translation apps to
determine their suitability for enabling everyday conversations in health care
settings.[6]
Machine translation for smartphones, mobile and computer devices featuring
translation capacities for input texts, messages, emails and so on includes many
useful features where the user can use mobile apps of translation whenever and
wherever and conducting discussions.[7]
The study recommends language instructors promote the use of the app as a mini
dictionary, and encourage language learners to use it as a resource to ensure
accurate spelling and pronunciation.[8]
To trial three mobile translation apps in the healthcare settingto address language
barriers in everyday care between healthcare staff and olderpeople with limited
English proficiency (LEP).[9]
the development of machine translation applications (APPs) based on artificial
intelligence (AI) for foreign language recognition and translation. [10]
REFERENCES
[1] Albrecht, U. V., Behrends, M., Matthies, H. K., & von Jan, U. (2013). Usage of
multilingual mobile translation applications in clinical settings. JMIR mHealth and
uHealth, 1(1), e2268.
[2] Chen, X., Acosta, S., & Barry, A. E. (2017). Machine or human? Evaluating
the quality of a language translation mobile app for diabetes education
material. JMIR diabetes, 2(1), e7446.
[3] Eqab, A., & Shanableh, T. (2017, November). Android mobile app for real-
time bilateral Arabic sign language translation using leap motion controller.
In 2017 International Conference on Electrical and Computing Technologies and
Applications (ICECTA) (pp. 1-5). IEEE.
[4] Gunarto, H. (2019). Apps-based machine translation on smart media devices-a
review. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 13(1),
95-104.
[5] Kothari, N., Jain, C. P., Soni, D., Kumar, A., Dadheech, A., & Sharma, H.
INSTANT LANGUAGE TRANSLATION APP.
[6] Panayiotou, A., Gardner, A., Williams, S., Zucchi, E., Mascitti-Meuter, M.,
Goh, A. M., ... & Batchelor, F. (2019). Language translation apps in health care
settings: Expert opinion. JMIR mHealth and uHealth, 7(4), e11316.
[7] Abdullah, A. H. (2020). The Linguistic Problem-based Effect of Using
Machine Translation in Mobile & Computer Apps: English and Arabic as a case
study. Al-Qalam journal, 4(8), 325-349.
[8] Bin Dahmash, N. (2020). ‘I Can't Live Without Google Translate’: A Close
Look at the Use of Google Translate App by Second Language Learners in Saudi
Arabia. Arab World English Journal (AWEJ) Volume, 11.
[9] Hwang, K., Williams, S., Zucchi, E., Chong, T. W., Mascitti‐Meuter, M.,
LoGiudice, D., ... & Batchelor, F. (2022). Testing the use of translation apps to
overcome everyday healthcare communication in Australian aged‐care hospital
wards—An exploratory study. Nursing open, 9(1), 578-585.
[10] Tang, J. (2024). Design and Implementation of Foreign Language Recognition
and Translation APP Based on Artificial Intelligence. Procedia Computer
Science, 243, 647-654.
Future Scope
Future for the translation will cover the many more cultures, as the internet
continues to penetrates in emerging countries worldwide. Besides all the top
languages for translation, the software will provide the accurate and exact solutions
for communicating with users who speak known language of them. Improved
speed and accuracy in real-time speech and text translation, enabling seamless
communication in meetings, conferences, and travel. Smart devices and assistants
capable of translating multiple languages in real-time, enhancing smart home
experiences and connectivity. Devices like smart glasses and earbuds equipped
with language translation features for on-the-go usage. Advanced systems that
preserve tone, emotion, and intent during speech translation. Businesses can enter
new markets by overcoming language barriers, improving customer experience and
engagement.
