Glossary

Translation productivity

Translation productivity is the measure of how efficiently linguistic content is converted from one language to another without compromising quality. It is typically calculated by the volume of words a linguist or workflow can process within a specific timeframe, driven by the effective use of technology, automation and linguistic assets.

Description

Historically, productivity was limited by human stamina. A professional translator might average 2,000 to 3,000 words per day. Today, CAT tools (Computer-assisted translation) have transformed that baseline. By leveraging Translation memory (TM), linguists never have to translate the same sentence twice. The system instantly retrieves previously approved translations for identical or similar segments (fuzzy matching), allowing the translator to focus only on new content.

The integration of Neural machine translation (NMT) has shifted the paradigm further. Instead of translating from scratch, linguists often act as editors (post-editors), reviewing and refining AI-generated output. This workflow, known as Machine translation post-editing (MTPE / post-editing), can boost productivity significantly. Beyond the linguist’s desk, productivity is also about Localization Workflow automation. Translation Management Systems (TMS) automate the "invisible work" of project management – file analysis, vendor assignment, file transfer and invoicing.

Related terms

CAT tools (Computer-assisted translation) Machine translation post-editing (MTPE / post-editing) Neural machine translation (NMT) TM leverage (translation memory leverage) Translation Management System (TMS) Translation memory (TM)

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