Xorijiy lingvistika va lingvodidaktika
–
Зарубежная
лингвистика
и
лингводидактика
–
Foreign
Linguistics and Linguodidactics
Journal home page:
https://inscience.uz/index.php/foreign-linguistics
Cultural transmission and adaptation in literary
translation
–
Machine Translation (MT) vs. Human
Translation (HT)
Bakhodir ABDIRASULOV
1
Samarkand State Institute of Foreign Languages
ARTICLE INFO
ABSTRACT
Article history:
Received March 2025
Received in revised form
10
April 2025
Accepted 2 April 2025
Available online
25 May 2025
This article examines the contrasting roles of Machine
Translation (MT) and Human Translation (HT) in the
transmission and adaptation of cultural elements in literature.
As literary translation requires not only linguistic accuracy but
also cultural sensitivity, the ability of MT to transfer such
complexity is limited. Through examples and case studies, this
paper compares the effectiveness of MT and HT in handling
cultural references, idioms, humor, and stylistic peculiarities. It
argues for the continued importance of human intervention in
literary translation, particularly when translating texts.
2181-3701
/©
2025 in Science LLC.
DOI:
https://doi.org/10.47689/2181-3701-vol3-iss5
/S
-pp17-22
This is an open-access article under the Attribution 4.0 International
(CC BY 4.0) license (
https://creativecommons.org/licenses/by/4.0/deed.ru
Keywords:
machine translation,
human translation,
children’s literature,
cultural adaptation,
literary translation,
translation challenges.
Badiiy tarjimada madaniy moslashuv: mashina va inson
tarjimalaridagi muammolar
ANNOTATSIYA
Kalit so‘zlar
:
mashina tarjimasi,
inson tarjimasi,
bolalar adabiyoti,
madaniy moslashuv,
badiiy tarjima,
tarjima muammolari.
Ushbu maqolada mashina tarjimasi va inson tarjimasining
adabiyotdagi
madaniy
elementlarni
ko‘chirish
va
moslashtirishdagi o‘zaro farqli rollari tahlil qilinadi
. Badiiy
tarjima nafaqat til jihatidan aniqlikni, balki madaniy sezgirlikni
ham talab etadi. Mashina tarjimasi esa bu murakkablikni
yetarlicha ifodalashda hali-hanuz cheklovlarga ega. Maqolada
misollar va amaliy tadqiqotlar asosida mashina va inson
tarjimalarining madaniy konnotatsiyalar, idiomalar, hazil
hamda stilistik xususiyatlarni yetkazishdagi samaradorligi
solishtiriladi. Shuningdek, bunday madaniy jihatdan boy
matnlarni tarjima qilishda inson omilining doimiy ahamiyatga
ega ekani ta’kidlanadi
.
1
Senior Teacher, Samarkand State Institute of Foreign Languages. E-mail: abdirasulov@samdchti.uz
Xorijiy lingvistika va lingvodidaktika
–
Зарубежная лингвистика
и лингводидактика
–
Foreign Linguistics and Linguodidactics
Special Issue
–
5 (2025) / ISSN 2181-3701
18
Культурная трансмиссия и адаптация в литературном
переводе: машинный перевод (МП) и перевод
человека (ПЧ)
АННОТАЦИЯ
Ключевые слова:
машинный перевод,
перевод человека,
детская литература,
культурная адаптация,
литературный перевод,
трудности перевода
.
В статье рассматриваются различия в подходах
машинного перевода (МП) и перевода человека (ПЧ) к
передаче и адаптации культурных элементов в
литературных произведениях. Поскольку литературный
перевод требует не только языковой точности, но и
высокой
степени
культурной
чувствительности,
возможности МП в передаче таких сложных аспектов
остаются ограниченными. На основе примеров и
тематических исследований проводится сравнительный
анализ эффективности МП и ПЧ в передаче культурных
реалий, идиом, юмора и стилистических особенностей.
Делается вывод о неизменной значимости участия
человека в процессе литературного перевода, особенно при
работе с насыщенными культурным контекстом текстами.
INTRODUCTION
The translation of literary texts involves more than just linguistic accuracy; it
requires the transmission of cultural meanings embedded in the original work.
Numerous studies have explored the role of translation in cultural adaptation, comparing
the effectiveness of machine translation (MT) and human translation (HT) in preserving
cultural elements. Literary translation is a multifaceted process that extends beyond the
direct conversion of words from one language to another. It encompasses the transfer of
cultural values, stylistic features, and emotional tones. In literature, where language is
playful, culturally rich, and often idiomatic, preserving cultural elements becomes a key
concern. With the growing use of Machine Translation (MT) tools such as Google
Translate and DeepL, questions arise about their capacity to handle such tasks.
LITERATURE REVIEW
Jeremy Munday in
“Introducing Translation Studies: Theories and Applications”
provides a foundational overview of translation theories, emphasizing cultural and
ideological considerations in translation. Peter Newmark, in
“A Textbook of Translation”,
distinguishes between communicative and semantic translation and addresses the
importance of cultural context. Lawrence Venuti, in
“The Translator’s Invisibility:
A History of Translation”,
argues for foreignization in translation to preserve source
culture elements and challenges the translator’s hidden role. Riitta Oittinen, in
“Translating for Children”,
explores the unique aspects of translating children’s literature,
including the influence of visuals, rhythm, and cultural adaptation. Christiane Nord, in
“Text Analysis in Translation”,
states for the functionalist Skopos theory, stressing the
purpose of translation in shaping outcomes. Antonio Toral and Andy Way, in their study
on neural machine translation for literary texts, examine the quality and challenges of
applying MT in literary contexts. Joss Moorkens and Sharon O’Brien co
ntribute
significantly to the field of MT post-editing and translation technologies, particularly in
user-centered and ethical approaches.
Xorijiy lingvistika va lingvodidaktika
–
Зарубежная лингвистика
и лингводидактика
–
Foreign Linguistics and Linguodidactics
Special Issue
–
5 (2025) / ISSN 2181-3701
19
MAIN PART
The concept of cultural transmission in translation has been widely discussed in
translation studies. Bassnett emphasizes that literary translation is not just a linguistic
transfer but also a cultural negotiation between the source and target languages. Toury
introduced the idea of descriptive translation studies, which highlights how translated
texts function within the target culture, often requiring adaptations to align with cultural
norms.
Children’s literature often includes elements that are deeply embedded in a
particular culture, including references to traditional foods, holidays, names, school
routin
es, and idiomatic expressions. For instance, Uzbek children’s literature may contain
references to
"beshik toy"
(cradle ceremony) or
"Navruz"
(spring festival), which carry
significant cultural meaning but may be unfamiliar to foreign readers. The translat
or’s
challenge is to either preserve these elements (foreignization) or adapt them to the
target culture (domestication). Both strategies require interpretive skill, especially when
the target audience comprises young readers with limited cultural awareness.
Machine translation (MT) tools generate automatic translations. Among the most
widely known are the free online translators such as Bing translator, Google Translate.
However, Hartley points out that MT is increasingly used for dissemination, for example
by the European Commission in order to provide a draft first translation of documents
which are then post-edited by a human translator or editor.
Human translators employ various strategies to ensure cultural meaning is
accurately conveyed. Baker identifies cultural equivalence as a key method used by
human translators to adapt texts without losing meaning. Additionally, Newmark
discusses the importance of contextual translation, where human translators adjust
meaning based on historical and social contexts.
MT, driven by AI and neural networks, is fast, cost-effective, and consistent.
However, it struggles with literature due to key issues: it often translates idioms literally,
lacks contextual and cultural understanding, mishandles humor and wordplay, and fails
to capture style and tone. Despite its progress, MT cannot yet replace the creative and
cultural depth required in literary translation.
HT offers cultural sensitivity, creativity, and audience awareness. Human
translators prioritize meaning, adapt cultural references, preserve humor and wordplay,
and consider the needs of young readers. These skills ensure that literature translations
remain lively, clear, and culturally relevant.
Research by Castilho et al. demonstrates that while MT performs well in technical
translations, it often fails to recognize and translate culturally loaded words. MT systems
tend to provide literal translations, which may distort the cultural significance of terms
such as Uzbek
mahalla
or Russian
samovar
.
Pym proposes that while MT can assist in the early stages of translation, human
intervention is necessary to refine translations and adapt cultural references. This aligns
with the post-editing approach, where human translators correct MT errors to enhance
readability and cultural accuracy.
Scientific/Technical Text (English):
"The CRISPR-Cas9 system enables targeted
genome editing by introducing double-strand breaks at specific DNA sequences, facilitating
precise gene modifications."
Xorijiy lingvistika va lingvodidaktika
–
Зарубежная лингвистика
и лингводидактика
–
Foreign Linguistics and Linguodidactics
Special Issue
–
5 (2025) / ISSN 2181-3701
20
Machine Translation (DeepL
–
Uzbek):
"CRISPR-
Cas9 tizimi aniq gen o‘zgarishlarini
osonlashtirib, muayyan DNK ketma-ketliklarida ikki zanjirli uzilishlarni kiritish orqali
maqsadli genom tahrirlashni amalga oshiradi."
Human Translation (Uzbek):
"CRISPR-Cas9 tizimi maqsadli genom tahririga imkon
yaratadi va DNKning ma’lum qismlarida o‘zgarishlar qilish orqali genetik
modifikatsiyalarni amalga oshiradi."
Translating scientific text MT performs well and more accurate than human
translation when comparing with human translators. Cultural adaptation is important in
the translation process. In this example, we will analyze translation of cultural elements
by HT and MT:
Extract from "Pride and Prejudice" by Jane Austen
Original Text:
“It is a truth universally acknowledged,
that
a single man
in
possession of a good fortune,
must be in want of a wife.
However little known the feelings or views of such a man may be on his first entering
a neighborhood, this truth is so well fixed in the minds of the surrounding families, that he is
considered the rightful property of someone or other of their daughters. 'My dear Mr.
Bennet,' said his lady to him one day, 'have you heard that Netherfield Park
is let at last?”
Machine Translation (Google Translator):
Hamma tan olgan haqiqat, boylikka
ega bo
‘
lgan
yolg
‘
iz erkak xotinga muhtoj bo
‘
lishi kerak.
Bunday odamning mahallaga
birinchi marta kirib kelganida qanday his-tuyg
‘
ulari yoki qarashlari kam ma
’
lum bo
‘
lmasin,
bu haqiqat atrofdagi oilalar ongida shunchalik mustahkam saqlanib qolganki, u u yoki bu
qizning haqli mulki hisoblanadi. Hurmatli janob Bennet,
–
dedi bir kuni unga xonim,
–
Niderfild Parkga nihoyat ruxsat berilganini eshitganmisiz?
Human Translation:
“Qolida puli bor
balog‘atga yetgan har bir yigit
o‘ziga qalliq
topishi
kerakligi hammaga ma’lum.
Agar shunday odam yangi joyga ko‘chib keladigan bo‘lsa, hali hech kim uning
rejalaridan xabardor bo‘lmay turiboq, yuqorida. Azizim mister Bennet,
–
dedi bir kuni
missis Bennet eriga,
–
Nezerfild park endi axiri
bo‘sh turmasligini eshitdingizmi?”
After analyzing both approaches, it becomes clear that Machine Translation (MT)
is more effective for technical texts where accuracy, consistency, and terminology are
prioritized over style or cultural nuance. In contrast, Human Translation (HT) is better
suited for
literary and children’s texts, as it allows for the creative adaptation of cultural
elements, idioms, and emotional tones to resonate with the target audience. Each method
serves different purposes, and their effectiveness depends on the text type and the
intended reader experience.
To illustrate the differences between MT and HT, this section presents selected
examples from children’s books translated into Uzbek. Each source sentence is followed
by its MT and HT versions, with commentary on cultural and linguistic effectiveness.
Idiomatic Expression
–
Source (English):
“Don’t cry over spilled milk,” said Tom’s mother.
–
MT (Uzbek):
“To‘kilgan sutga yig‘lamang,” dedi Tomning onasi.
–
HT (Uzbek):
“Bo‘lib o‘tgan ishga kuyinmang,” dedi Tomning onasi.
MT's version is literal and unnatural. HT uses a culturally equivalent phrase that
children can understand, preserving the intended meaning.
Cultural Reference (Food)
–
Source:
“She handed him a peanut butter and jelly sandwich.”
Xorijiy lingvistika va lingvodidaktika
–
Зарубежная лингвистика
и лингводидактика
–
Foreign Linguistics and Linguodidactics
Special Issue
–
5 (2025) / ISSN 2181-3701
21
–
MT:
“U unga yer yong‘oqli va jeleli sendvich berdi.”
–
HT:
“U unga yong‘oq va murabbo surilgan non berdi.”
The MT version uses unfamiliar loan words. HT adapts the sentence to reflect food
items known to Uzbek children.
Humor and Wordplay
–
Source:
“Why did the banana go to the doctor? Because it wasn’t feeling well!”
–
MT:
“Nima uchun banan shifokorga bordi? Chunki u o‘zini tozalay olmayapti!”
–
HT:
“Nega banan vrachga bordi? Chunki u o‘zini yaxshi his qilmayapti –
po‘stlog‘i
yomon edi!”
MT misses the pun entirely. HT reconstructs the joke with a clever word choice
that makes sense in the target language.
These examples demonstrate that while MT may be functional for basic
translation, it lacks the interpretive capacity necessary for literary and cultural
adaptation.
Original Sentence:
“Bugun havo juda issiq, lekin kechqurun salqin bo‘ladi”
Human Translation:
“Today the weather is very hot, but it will be cool in the
evening”
Machine Translation (Yandex Translate):
“Today the weather is very hot, but in
the evening, it will be cool”
Refine the machine translation:
“Today the weather is very hot, but it will cool
down in the evening.”
(Even more natural!)
Comparing MT and HT in literary translation suggests that while MT is improving,
it still lacks cultural sensitivity. van den Bosch and Daelemans (2013) argue that even
advanced MT models struggle with humor, irony, and cultural wordplay, elements that
human translators handle more effectively.
Pym proposes that while MT can assist in the early stages of translation, human
intervention is necessary to refine translations and adapt cultural references. This aligns
with the post-editing approach, where human translators correct MT errors to enhance
readability and cultural accuracy.
CONCLUSION
While Human Translation (HT) still outperforms Machine Translation (MT) in the
realm of literature, especially in conveying cultural depth, emotional tone, and stylistic
aspects, human translators have a great role in refining culturally sensitive and
linguistically rich passages. As seen in the examples discussed, MT often struggles with
idiomatic expressions, humor, and culturally embedded references, resulting in
translations that miss the intended meaning or emotional impact. Custom-trained MT
systems, using literary corpora, hold potential for improved performance, but the
inherently creative and interpretive nature of literary translation. The reviewed
literature reinforces this view, emphasizing the importance of HT in preserving cultural
aspects and engaging young readers in a meaningful way. While MT offers advantages in
speed and cost, it cannot yet replicate the cultural sensitivity and imaginative quality that
define effective children's literature translation. Thus, the future of literary translation
likely lies in a balanced synergy between machine efficiency and human creativity, with
human translators remaining essential to the cultural and emotional authenticity of the
final text.
Xorijiy lingvistika va lingvodidaktika
–
Зарубежная лингвистика
и лингводидактика
–
Foreign Linguistics and Linguodidactics
Special Issue
–
5 (2025) / ISSN 2181-3701
22
REFERENCES:
1.
Baker, M. (1992).
In Other Words: A Coursebook on Translation
. Routledge.
2.
Bassnett, S. (2014).
Translation Studies
(4th ed.). Routledge.
3.
Castilho, S., Moorkens, J., Gaspari, F., & Way, A. (2017). "Is Neural Machine
Translation the New State of the Art?"
The Prague Bulletin of Mathematical Linguistics
,
108(1), 109-120.
4.
Newmark, P. (1988).
A Textbook of Translation
. Prentice Hall.
5.
Pym, A. (2010).
Exploring Translation Theories
. Routledge.
6.
Toury, G. (1995).
Descriptive Translation Studies and Beyond
. John Benjamins.
7.
Toral, A., & Way, A. (2018). "What Level of Quality Can Neural Machine
Translation Attain on Literary Text?"
Translation Quality Assessment
, 1-18.
8.
Munday, J. (2016). Introducing Translation Studies: Theories and Applications
(4th ed.). Routledge.
9.
Moorkens, J. (2018). Post-editing of machine translation: Processes and
applications. In J. Moorkens, S. Castilho, F. Gaspari, & S. Doherty (Eds.), Translation
Quality Assessment: From Principles to Practice (pp. 59
–
86). Springer.
10.
Jane Austen Pride and Prejudice. E-BooksDictary.com. 1813. P. 538.
11.
Jane Austen Pride and Prejudice, translated by Muhabbat Ismoilova. Toshkent:
Yangi asr avlodi. 2017. P.406.
12.
Rustamovna, H. F. (2020). KEY CONCEPTS OF SIMULTANEOUS TRANSLATION.
В научный сборник вошли научные работы, посвященные широкому кругу
современных проблем науки и образования, вопросов образовательных
технологий 2020.
-
436 с., 232
.
13.
Халимова, Ф. (2017). Поэтик таржимада эквивалентлик ва адекватлик
тушунчаси. Иностранная филология: язык, литература, образование,
2(2), 63.
14.
Халимова, Ф. Р. (2021). КОГНИТИВ
ПОЭТИКА
. Academic research in
educational sciences, 2(12), 133-142.
