{"id":8990,"date":"2026-03-24T13:43:11","date_gmt":"2026-03-24T13:43:11","guid":{"rendered":"https:\/\/gft.goweblab.com\/?page_id=8990"},"modified":"2026-05-21T08:18:01","modified_gmt":"2026-05-21T08:18:01","slug":"machine-translation","status":"publish","type":"page","link":"https:\/\/gft.goweblab.com\/en\/machine-translation\/","title":{"rendered":"Machine Translation"},"content":{"rendered":"\t\t
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Machine Translation<\/h1>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Machine translation involves translating a text using a computer (or AI) without human interaction.\n<\/p>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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What to<\/span> expect.<\/span><\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Machine translation (MT) has developed rapidly in recent years and is now an indispensable part of a translation agency\u2019s standard repertoire. The industry even suspects that AI-generated translations will soon reach the quality of human translations. <\/span>
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<\/span>This could mean that human translators will soon be replaced, even in specialized translation. However, this could still be a long way off, as purely machine translation systems without human support are still too prone to errors. So, how is machine translation currently being used effectively?<\/span><\/p>

Machine translation is now part of modern language workflows. For businesses handling high volumes, tight deadlines or regularly updated content, it can reduce turnaround times and improve scalability.<\/span><\/p>

That said, machine translation without human validation remains vulnerable to context errors, terminology drift, nuance loss and compliance risks. The safest approach is to combine it with professional post-editing, approved glossaries and clearly defined quality criteria.<\/strong><\/p><\/div><\/div><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Request a non-binding offer now!<\/span><\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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We are happy to help you make your international business and processes efficient and secure with high-quality translations. May we assist you? Then request a free, no-obligation quote now.<\/p>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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What you can expect from<\/span>
Machine translation?<\/span><\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Machine translation can now speed up multilingual projects, reduce repetitive effort and support teams working with large content volumes.<\/span><\/p>

But final quality still depends on three core factors: source-text quality, how well the engine fits the domain, and the level of human review applied after translation.<\/span><\/p>

That is why the right question is not whether machine translation replaces translators. It is when to use it and how much post-editing is needed.<\/b>
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Machine Translation for Business<\/h3>

Machine translation is the use of software or AI to translate text without human intervention in the first draft. Its real business value appears when that technology is integrated into a process with approved terminology, clear quality goals and human review matched to the risk level of the content.<\/span><\/p>

At GFT, we help companies use machine translation in a controlled way, with human post-editing, terminology management and workflows designed for technical, operational, internal and customer-facing content.<\/span><\/p>

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Rule-based systems\n<\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Rule-based systems use grammars, dictionaries and predefined linguistic rules to generate translations. They can be useful where terminology control is strong and the domain is highly structured, but they often sound less natural.<\/span><\/p>

Their main advantage is lexical consistency. Their main limitation is fluency and contextual adaptability.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Statistical MT systems<\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Statistical systems learn from large bilingual datasets and choose translations based on probability. They usually produce more fluent output than rule-based systems, but they are less dependable in specialised terminology.<\/span><\/p>

They play a smaller role today than neural machine translation, yet they remain useful for understanding how the technology has evolved.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Neural MT systems<\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Neural machine translation uses neural networks trained on large datasets to interpret context, language patterns and relationships between sentences.<\/span><\/p>

It is currently the best-performing approach for many language pairs. Even so, it does not remove the risk of omissions, wrong terminology, hallucinations or poor nuance handling, especially in specialised content.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Machine translation vs translation memory\n<\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Machine translation generates a new translation from a language model. Translation memory reuses previously approved segments from earlier projects to support human translators.<\/span><\/p>

In a professional workflow, the two technologies complement each other. Translation memory strengthens consistency and reuse; machine translation speeds up production when paired with human review.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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The prerequisites for high-quality machine translations<\/span><\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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A key prerequisite for high-quality machine translation is the quality of your source text. If it already contains numerous errors, these will be carried over by the AI \u200b\u200bin the target language. This isn’t just about correct grammar, flawless spelling, or punctuation.\u00a0<\/span>Writing in a translation-friendly style<\/span><\/a>\u00a0is particularly helpful , as it prevents some errors from occurring in the first place. This also includes good\u00a0<\/span>terminology management<\/span><\/a>\u00a0within your company, which is comprehensively documented in a database.<\/span><\/p>

While writing in a way that facilitates translation is already a crucial factor for translation quality in human translation, it plays an even greater role in machine translation. The more structured and logical a source text is, the fewer problems a machine translation system will have with accurately rendering it in the target language.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t

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How machine translation engines learn\n<\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Machine translation engines improve through relevant, well-cleaned bilingual data. Rather than relying on volume alone, the real differentiator is data quality and closeness to your domain.<\/span><\/p>

For business content, a well-configured engine needs approved terminology, real sector examples and quality goals aligned with the intended use of the text.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Engine training\n<\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Training a machine translation engine means exposing it to high-quality source and target sentence pairs. The better the data, the more useful the output becomes for your domain.<\/span><\/p>

Not every project requires a dedicated engine, but the more specialised the content, the greater the potential value of customisation.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Post-editing under ISO 18587\n<\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Post-editing is the professional review of text generated by machine translation. ISO 18587 sets requirements for post-editing machine-translated output and underlines the need for qualified linguists, clear processes and defined quality goals.<\/span><\/p>

For businesses, that means the speed of technology should be matched by linguistic accountability.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Light post-editing\n<\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Light post-editing fixes critical errors in meaning, terminology or readability, but it does not aim to reach the stylistic standard of a fully human translation.<\/span><\/p>

It is a suitable option for internal content, short-lived documentation or workflows where the main goal is fast and sufficient understanding.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Full post-editing<\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Full post-editing revises the text until it reaches a quality level close to what would be expected from a professional translation for publication, external communication or sensitive documentation.<\/span><\/p>

It is the right choice when brand impact, customer experience, compliance or operational risk do not allow compromises.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Machine translation with full post-editing<\/span><\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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This free checklist explains how it works!<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t
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Limits of <\/span>machine translation.<\/span><\/h2>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In fact, machine translation (MT) systems have advanced to the point where machine translation of general-language source texts works almost flawlessly. A fundamental requirement is that the AI \u200b\u200bis trained using large datasets. However, even the best MT system cannot guarantee that a machine-translated text is error-free. In many areas, the human factor still plays the most significant role. Translation errors are particularly likely when the operators of the MT system have little or no command of the target language.<\/span><\/p>

Source of error: homographs<\/span><\/h4>

A major danger with machine-translated texts lies in an inconspicuous detail: homographs. These are words that have the same spelling but different meanings. Many rule-based and statistical MT systems cannot actually interpret the correct meaning of a homograph in such cases \u2013 whether a translation is correct is therefore purely a matter of chance. Here are some examples:<\/span><\/p>
Word<\/span><\/strong><\/td>1.\u00a0\u00a0\u00a0\u00a0<\/span><\/strong>Meaning<\/span><\/strong><\/td>2.\u00a0\u00a0\u00a0\u00a0<\/span><\/strong>Meaning<\/span><\/strong><\/td><\/tr>
translate<\/span><\/td>translated into another language<\/span><\/td>go to the other side<\/span><\/td><\/tr>
modern<\/span><\/td>contemporary (adj.)<\/span><\/td>rot (verb)<\/span><\/td><\/tr>
seven<\/span><\/td>Number<\/span><\/td>filter, extract (verb)<\/span><\/td><\/tr>
Bug<\/span><\/td>Ship part<\/span><\/td>Programming error (translated into German)<\/span><\/td><\/tr>
Assembly<\/span><\/td>Day of the week (plural)<\/span><\/td>Assembly (Germanized)<\/span><\/td><\/tr><\/tbody><\/table>

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Neural machine translation systems represent an exception to the error-proneness associated with homographs. If these systems have been trained and fed large datasets beforehand, they can easily distinguish between the different meanings of a homograph. They infer the appropriate meaning from the context and then translate it into the correct equivalent in the target language.<\/span><\/p>

Problems and opportunities of MT systems in specialized translations<\/span><\/h4>

In general, the risk of serious errors in specialized translations is increased simply due to the potential for incorrect application of the machine translation (MT) system. Furthermore, machine translations are of little use for texts in the fields of marketing or literature, regardless of the operator’s skill and experience. This is because linguistic nuances, idioms, and wordplay are often completely lost in the process. A literary masterpiece in Japanese can then degenerate into an emotionless novel in German.<\/span><\/p>

Machine translation of legal, technical, or medical texts is possible. However, we advise against using machine translation without subsequent proofreading: You bear a high risk of resulting translation errors. Furthermore, many legal uncertainties still exist in the field of machine translation. For example, who assumes responsibility and liability for personal injury or property damage resulting from an error in a machine-translated text? If you prefer not to venture into this uncertain territory, you should probably rely on the services of a human translator.<\/span><\/p>

Despite this, machine translation holds enormous potential in many of these specialized fields. Neural machine translation followed by post-editing by a subject-matter expert is already a viable and sensible alternative to human translation.<\/span><\/p><\/div><\/div><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Have a <\/span>question?
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Simply contact us, and we will schedule a consultation to discuss your project and how we can help bring your vision to life.<\/p>\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\tWhat is machine translation (MT)?<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/i><\/span>\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t<\/p>\t\t\t\t<\/div>\n\n\t\t\t\t

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Machine translation is the automated translation of text using AI or computer-based systems without human input during the initial translation process.\u00a0<\/span><\/p><\/div><\/div>\t\t\t\t<\/div>\n\n\t\t\t\t<\/div>\n\n\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t

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\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\tWhat are the main types of machine translation?<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/i><\/span>\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t<\/p>\t\t\t\t<\/div>\n\n\t\t\t\t

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There are three main types: rule-based MT, statistical MT and neural MT. Neural machine translation is currently the most advanced, as it considers context rather than translating word by word.\u00a0<\/span><\/p><\/div><\/div>\t\t\t\t<\/div>\n\n\t\t\t\t<\/div>\n\n\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t

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\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\tIs machine translation accurate enough for professional use?<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/i><\/span>\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t<\/p>\t\t\t\t<\/div>\n\n\t\t\t\t

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Machine translation can produce good results for general content, but it is still prone to errors, especially in specialized or sensitive texts. Human review is essential to ensure accuracy and reliability.\u00a0<\/span><\/p><\/div><\/div>\t\t\t\t<\/div>\n\n\t\t\t\t<\/div>\n\n\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t

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\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\tWhat is post-editing in machine translation?<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/i><\/span>\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t<\/p>\t\t\t\t<\/div>\n\n\t\t\t\t

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Post-editing is the process of reviewing and correcting machine-translated content by a professional translator to improve accuracy, clarity and style.\u00a0<\/span><\/p>



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\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\tWhat is the difference between machine translation and translation memory?<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/i><\/span>\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t<\/p>\t\t\t\t<\/div>\n\n\t\t\t\t

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Machine translation generates new translations automatically, while translation memory stores and reuses previously translated content to support human translators and ensure consistency.\u00a0<\/span><\/p><\/div><\/div>\t\t\t\t<\/div>\n\n\t\t\t\t<\/div>\n\n\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t

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\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\tWhen should machine translation be used?<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/i><\/span>\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t<\/p>\t\t\t\t<\/div>\n\n\t\t\t\t

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Machine translation is suitable for large volumes of content, internal documents or time-sensitive projects. For high-quality, client-facing or specialized content, it should always be combined with professional post-editing.<\/span><\/p><\/div><\/div>\t\t\t\t<\/div>\n\n\t\t\t\t<\/div>\n\n\t\t\t<\/div>\n\t\t\t\t\t\t\n\t\t<\/div>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Machine Translation Machine translation involves translating a text using a computer (or AI) without human interaction. What to expect. Machine translation (MT) has developed rapidly in recent years and is now an indispensable part of a translation agency\u2019s standard repertoire. The industry even suspects that AI-generated translations will soon reach the quality of human translations. […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-8990","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/gft.goweblab.com\/en\/wp-json\/wp\/v2\/pages\/8990","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gft.goweblab.com\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/gft.goweblab.com\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/gft.goweblab.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/gft.goweblab.com\/en\/wp-json\/wp\/v2\/comments?post=8990"}],"version-history":[{"count":0,"href":"https:\/\/gft.goweblab.com\/en\/wp-json\/wp\/v2\/pages\/8990\/revisions"}],"wp:attachment":[{"href":"https:\/\/gft.goweblab.com\/en\/wp-json\/wp\/v2\/media?parent=8990"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}