Translation memory, often shortened to TM, is a store of previously translated text segments that can be reused when the same or similar source text appears again. Instead of retranslating repeated sentences from scratch, a translation system or linguist can retrieve the prior approved version and decide whether it still fits.
Why It Matters In AI
Modern AI translation services get stronger when they combine model output with reusable bilingual assets. That is why translation memory often sits next to machine translation, glossaries, adaptive translation, and review workflows. TM helps keep terminology, recurring product language, legal boilerplate, and support content stable over time.
What Good Use Looks Like
Good TM use is not blind copy-paste. Strong teams version their assets, keep domain boundaries clear, track when a segment was approved, and still review partial or fuzzy matches before publishing them. AI can help surface likely matches, suggest updates, and combine TM with glossary or style rules, but humans still decide when reuse is appropriate.
Where You See It
Translation memory is most visible in localization programs, enterprise translation services, legal and technical document workflows, multilingual support content, and any environment where the same phrases appear repeatedly across releases, policies, manuals, or product catalogs.
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Related concepts: Machine Translation, Cross-Lingual Information Retrieval, Automatic Speech Recognition, Speech Synthesis, Digital Accessibility, and Text Summarization.