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Localization

Machine Translation

Machine translation automatically converts text into another language using statistical or neural language models.

Machine translation automatically converts text into another language using statistical or neural language models. Technology, content, and processes must account for language, region, search behavior, and local conventions together. The concept is closely related to Translation Management and Localization.

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Translation Management

Localization

Content Audit

FAQ

Machine Translation

Is machine-translated content a risk for SEO?
Content published in bulk without review or added value can endanger visibility, since search engines aim at helpful content regardless of how it was produced. Reviewed translations backed by their own keyword research are uncritical. Quality, usefulness, and clean language versions matter, not the tool.
What does post-editing mean in machine translation?
Post-editing means that language professionals review and correct a machine translation. The effort depends on the quality bar: a light pass for internal content, a thorough revision for campaigns. It combines speed with editorial accountability. Without a defined quality level, the effort is hard to plan. Clear terminology lists reduce the number of corrections considerably.
How good is machine translation for websites?
Neural translation produces readily understandable drafts for many language pairs but makes errors with technical terms, tone, and ambiguity. For marketing copy and legally relevant content, it is not sufficient without review. A workflow in which people proofread results and define terminology makes sense.