In recent years, machine translation has evolved from primitive dictionaries to complex neural network systems capable of translating texts into hundreds of languages in a matter of seconds. Today, it is used by millions of people: at work, while traveling, in correspondence, and in documents. Companies are automating localization, startups are integrating translation into their products, and translation agencies are incorporating machine translation into their processes.
But the main question remains: can machine translation technology really replace professional translators? Where is the line between the capabilities of machines and the unique value of human knowledge? Let's figure it out together.
The Definition of Machine Translation
Machine translation is a technology that automatically converts text from one language to another using special software. The most common approach today is neural machine translation (NMT). It is based on deep neural networks that are trained on large parallel data corpora. This approach allows for context, structure, and overall meaning to be taken into account.
In practice, the capabilities of MT are impressive. For example, Lingvanex translates up to 20,000 characters per second, supports hundreds of languages, including rare ones, and remains affordable even for large volumes of work. This makes machine translation particularly effective for corporate documentation, business correspondence, websites, user interfaces, and voice messages. It is especially useful in situations where high speed and efficiency are critical. In addition, such systems allow for the effective processing of large amounts of information.
Another popular translation method is translation using large language models (LLMs). They are capable of not only translating text, but also interpreting its content. This brings the quality of automatic translation even closer to that of human translation.
Advantages of Machine Translation
Machine translation has become an important tool in modern workflows, from rapid localization to processing large volumes of documents. The key reasons why companies and individual users choose this tool include:
- Cost. In many cases, machine translation is free. Even paid solutions are significantly cheaper than the services of translation agencies. Their cost is often lower than translating just a few documents with a professional translator. Human translation is more expensive because it requires considerably more time and effort.
- Efficiency. The speed of machine translation is incomparable to that of a professional translator. A human translator may spend anywhere from several days to several weeks or even months on a translation. Modern technologies have made the translation process almost instantaneous. As mentioned earlier, Lingvanex local software processes tens of thousands of characters per second.
- Consistency. Machine translation programs are consistent when translating repeated phrases and terms, which is crucial for technical, legal, and business documents. When large volumes of text are translated by humans, the work is usually distributed among several specialists, which can lead to differences in style and terminology across sections. With machine translation, a glossary of specialized terms can be uploaded in advance, and the model can even be customized for a narrow domain, such as medicine, law, finance, or technical translation. This makes it possible to maintain consistent terminology and high accuracy throughout the entire text.
- Geographical Accessibility. Online machine translation services are available anywhere there is mobile or satellite connectivity. Of course, one can take a human translator to another country, but this is extremely expensive. Contacting a trusted translation agency abroad can also be difficult due to time zone differences.
- Offline Translation. With Lingvanex local software, documents can be translated without an internet connection. This is convenient when working in areas with limited connectivity and helps protect confidential data. Local machine translation solutions generally give users more control over the process and their data.
- Supported Languages. Advanced machine translation systems work with more than a hundred languages, from Afrikaans and Albanian to Welsh and Zulu. Not every agency in Europe, Africa, or the Americas can quickly provide a human translator who speaks a less common language such as Mongolian. Yet Mongolia is not a small country, and more than 8 million people speak Mongolian.
- Confidentiality. When using machine translation, it is important to understand that only local, on-premise solutions deployed within the customer’s infrastructure can truly guarantee data security and confidentiality. In this case, source texts and their translations remain under the company’s control and do not leave the protected network. Online services that send data to the cloud cannot ensure complete confidentiality and security, as information is transmitted to third-party servers.
Despite the significant advantages of machine translation, it also has a number of limitations. Let’s take a closer look at them.
Limitations of Machine Translation
The aspects that machine translation still struggles with are precisely the areas where professional translators excel. Each limitation of the technology highlights situations in which human experience and expertise become a competitive advantage.
- Lack of Understanding of Cultural Context. Machines do not possess the cultural knowledge of native speakers. They may incorrectly convey culture-specific concepts, allusions, and wordplay. For example, in Russian, the expression «делать из мухи слона» literally translates as «to make an elephant out of a fly», but the correct English equivalent is «to make a mountain out of a molehill». Another example is «День Победы» (Victory Day, May 9), a major public holiday in Russia commemorating the end of World War II. A proper translation must convey the significance of the holiday to make the text understandable and relevant to English-speaking readers.
- Problems with Idioms and Fixed Expressions. For example, the Russian idiom «бить баклуши» literally translates as «to beat the baklushi» (pieces of wood used in old crafts), but the correct English equivalent is «to loaf around» or «to goof off». Another example is the Russian proverb «Без труда не вытащишь рыбку из пруда» can be translated as «Without effort, you can’t pull a fish out of the pond». A literal translation makes little sense in English, whereas the English equivalent «The early bird catches the worm» conveys the same idea: success comes to those who act promptly and work hard.
- Difficulties with Homonyms and Polysemous Words. Some English words have multiple meanings, which makes translation challenging. For example, the word «bat» can mean «a flying mammal» or «a piece of sports equipment used in baseball or cricket». Without context, a machine might choose the wrong meaning, producing a confusing or incorrect translation.
- Creativity. Translators can take a creative approach, especially when working with literary texts, poetry, or marketing materials. They use literary devices such as epithets, metaphors, similes, alliteration, and rhyme to more accurately convey the atmosphere and style of the original. Machine translation is not yet capable of conveying the emotional tone of a text in the way a human can.
How Professionals Use Machine Translation in Practice
In modern translation agencies, machine translation is actively integrated into the workflow as the first stage of text processing. The process usually looks like this: the text is loaded into CAT tools, then goes through a machine translation system, after which editors and proofreaders bring the material to a high-quality, ready-to-use state. This approach combines the speed of technology with the accuracy of human expertise.
Machine translation significantly saves time on preparing a draft. Instead of translating the entire text manually from scratch, the specialist receives a basis that can be quickly edited and adapted to the required style and terminology. Human verification remains a key stage, ensuring the accuracy of semantic nuances and compliance with professional standards.
In addition, the use of translation memories and glossaries allows for consistency in terminology and style in large projects. These tools record previously agreed-upon translations and recommendations for the use of terms, which is especially important for corporate texts and technical documentation. This makes the process not only fast, but also predictable in terms of quality.
Machine Translation Post-Editing (MTPE)
Machine translation offers speed and scalability, but even the best models still make semantic and stylistic errors. That is why we consider post-editing separately, because without it, automatic translation becomes a source of potential risks for businesses. This is especially critical in areas where accuracy affects reputation or legal consequences: medicine, law, and financial services.
Post-editing (MTPE) is a process in which a specialist editor refines text created by a machine translation system. The editor corrects errors, clarifies meaning, and adapts the style to the project requirements. In essence, it is a hybrid model that combines the speed of machine translation with human expertise. Post-editing allows you to get a high-quality result much faster than with a complete manual translation.
In the translation industry, there are two main MTPE approaches:
- Light Post-Editing. This approach focuses on correcting major errors: incorrect terminology, broken sentence structure, and factual inconsistencies. Its main goal is to make the text clear and accurate with minimal time investment.
- Full Post-Editing. This involves in-depth text refinement. The editor aligns the style, adapts the tone, takes context into account, and thoroughly checks terminology. The result is comparable to a professional human translation.
Today, MTPE is becoming the industry standard because it provides the optimal balance between speed, cost, and quality. Companies are able to translate large volumes of material faster while maintaining a high level of accuracy. This is also an important skill for translators. The ability to work competently with machine translation allows them to use technology more effectively and increases their competitiveness in the market.
The Balance Between Machine and Human: Is It Possible?
The balance between machine translation and human work is not only possible, it has become the standard in the modern translation industry. Machine systems take on the routine and voluminous part of the process, creating a rough draft of the text in a matter of seconds. This allows the translator to immediately move on to the meaningful work: analysis, clarification of terms, adaptation of style, and correction of errors. They also correct errors that machine translation algorithms inevitably make when encountering ambiguous words, idioms, fixed expressions, or puns.
The human contribution remains crucial because translation is not only about conveying words, but also interpreting meaning. The translator takes into account tone, genre, audience characteristics, text objectives, and cultural nuances that are not yet accessible to artificial intelligence. The collaboration between humans and technology combines the speed and scalability of machine translation with the accuracy and expressiveness that only a professional translator can provide.
Conclusion
The question of whether machine translation can completely replace professional translators remains open. Although modern machine translation systems are effective at handling simple and neutral texts, they are still unable to convey complex linguistic nuances, take context and cultural characteristics into account with the same level of accuracy as a human. Professional translators have experience, knowledge in specific fields, and an intuitive feel for language that allows them to produce accurate translations of even the most difficult materials. The harmonious interaction of AI and human knowledge is becoming the key to producing high-quality translations in the context of globalization.
