English_Borrowings_in_Russian_Translation_Errors_and_Machine_Translation_Challenges

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English Borrowings in Russian
Translation Errors & Machine Challenges
[F.I.O.]

2.

Globalization & Language
Unprecedented Scale
English influence on Russian is massive and accelerating.
Translation Risks
Rapid borrowing creates high potential for
misunderstanding.
Critical Impact
Errors in military/professional contexts can be dangerous.
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3.

Borrowed Words: 4 Key Domains
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IT Sphere
Business
Browser, Device, Software, Hacker
Manager, Startup, Deadline, Brand
Everyday Life
Military
Blogger, Poster, Shopping, Coach
Blockade, Schipper

4.

Context Determines Correct Translation
English Word
Accurate
Magazine
Physician
Critical Insight
Literal translation often leads to comical or critical
errors. Context is the absolute key to correct word
interpretation in professional environments.
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Correct Context
Точный
Common Error
Аккуратный
"We need accurate data."
Журнал
Магазин
"A fashion magazine."
Врач / Терапевт
"See a physician."
Физик

5.

False Friends of the Translator
"False friends" are words that look similar to Russian words but have completely different
meanings, leading to critical errors.
Critical Insight
Even advanced language users are not immune to these errors. The visual
similarity creates a cognitive trap that bypasses critical checking.
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6.

Algorithms Cannot Grasp Subtle Context
Systems like Google Translate and DeepL struggle when context contradicts statistical
probability.
Literal Translation of Idioms
"It's raining cats and dogs"
С неба падают кошки и собакиЛьет как из ведра
Professional Vocabulary
"Shell" (in IT context)
СкорлупаКомандная оболочка
Polysemy & Context
Machine translation relies on statistics, often missing the nuance of human
language.
"Novel" (outdated meaning: new)
Роман (Book)Новшество (Innovation)
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Experimental Design: Humans vs. Machines
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Participants
Military Academy Students
(2nd Course, 3rd Company)
Tested Systems
Google Translate, Yandex.Translate, DeepL
Target Vocabulary (10 Words)
Accurate
Complexion
Magazine
Prospect
Physician
Fabric
Sympathetic
Intelligent
Data
Camera
Testing Environment: Military Academy Classroom

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Human Translation Results
High Accuracy (>80%)
Students excelled with common words like Accurate, Magazine, and Data.
Familiarity drives performance.
Contextual Difficulties (40-60%)
Less frequent words like Fabric and Intelligent caused confusion when
used in specific contexts.
Critical Failures (<30%)
Specialized terms like Camera (legal: "in camera") resulted in near-total
failure, highlighting the danger of specialized vocabulary.
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Machine Translation Results
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Statistical Dominance
Algorithms excel at high-frequency vocabulary (98%+ accuracy)
where training datasets are vast.
The Context Gap
Performance drops significantly for polysemous words. Translators
default to the most statistically probable meaning, ignoring specific
context.
DeepL Advantage
DeepL shows better context handling than Google/Yandex, but still
fails with highly specialized terminology like "Camera" (legal).

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Humans and Machines: Error Patterns
Humans
Strengths
Machines
Strengths
Superior understanding of cultural context, idioms,
Excellent consistency with high-frequency
and nuance. Can infer meaning even when words
vocabulary. Rapid processing of large volumes of
are ambiguous.
text based on statistical models.
Weaknesses
Weaknesses
Vulnerable to specialized vocabulary gaps and "false
Fails when context contradicts statistics. Cannot
friends" if not specifically trained in the domain.
"understand" meaning, only predict word
probability.
Neither system is reliable alone. Human verification is required to bridge the gap between statistical
probability and contextual reality.
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Professional Translation Remains Essential
Human Critical Thinking
Linguistic erudition and judgment cannot be replaced by algorithms.
Cultural Context
Background knowledge is crucial for accurate interpretation of meaning.
Contextual Nuance
Professionals understand both statistical patterns and specific situational needs.
Effective Cross-Cultural Communication
Strategic Insight: Machine translation is a tool for initial drafts, not the final authority. It
requires mandatory verification by a qualified specialist.
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Conclusions and Recommendations
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Persistent Risk
The problem of "false friends" remains critical. Visual similarity creates dangerous
cognitive traps for both novices and experts.
Machine Limitations
Algorithms are powerful but blind to nuance. They cannot replace the linguistic erudition
required for professional translation.
Mandatory Verification
Machine translation must be treated as a draft. Subsequent verification by a qualified
specialist is non-negotiable.
Final Recommendation
"For effective cross-cultural communication, literal translation must be avoided in favor of context-aware interpretation."