1. When is machine translation useful?
Machine translation is particularly suitable for large volumes of text with recurring patterns, such as technical documentation, product descriptions, or internal communication. It quickly delivers raw translations that an experienced post-editor can efficiently optimize. When texts are clear, factual, and have little ambiguity, MT often yields acceptable results. Additionally, error rates are lower for language pairs with similar structures (e.g., German-English). However, avoid MT for creative, emotional, or highly culture-specific content, as nuances may be lost.
2. Where machine translation reaches its limits
Machine translation often fails with metaphors, irony, wordplay, or implicit cultural references. Specialized terminology in highly specific fields (medicine, law) also requires precise post-editing interventions. Quality drops significantly for rare language pairs or dialects. Additionally, text types such as marketing slogans, poems, or legal contracts require extensive post-editing and human expertise. Limitations also arise from data protection concerns with cloud-based systems.
3. Post-Editing: Light vs. Full
Light post-editing aims at minimal corrections: it removes obvious errors, ensures correct grammar and readability, but neglects style and idiomatic expressions. It is suitable for internal documents or texts with a short shelf life. Full post-editing, on the other hand, strives for a linguistically and stylistically flawless result that matches the quality of human translation. This is required for publications, marketing materials, and customer communication. The effort varies depending on the source material and language pair, but can be up to 100% of the time needed for a new translation.
4. Quality Assurance in Post-Editing
Quality assurance begins with the selection of a suitable MT system and preparation of the source texts (short sentences, consistent terminology). After post-editing, a review by a second linguist or subject matter expert follows. Proven methods include the use of terminology databases, style guides, and checklists. Automatic quality metrics (BLEU, TER) also provide indications of errors but do not replace human control. For sensitive content in particular, a multi-stage review process is recommended. The effort should be proportionate to the text's purpose.
5. Special Limitations for Marketing and Legal Texts
Marketing texts thrive on emotions, wordplay, and brand voice – machine translation usually misses this effect. Even full post-editing requires high creativity and cultural understanding here. Legal texts, on the other hand, demand legal precision; errors can entail liability risks. MT often delivers literal, inaccurate translations of clauses or technical terms. Therefore, for these text types, human translation followed by legal review is generally recommended. This does not replace legal advice from a qualified lawyer.
