Practice English vocabulary for translation memory (TM): stored segments, fuzzy matches, leverage, TM hits, and maintaining clean translation memories.
0 / 15 completed
1 / 15
What does 'the TM stores previously translated segments' mean?
Translation Memory stores source-target segment pairs. When a new text is submitted for translation, the TM is queried for matches. Reusing approved translations improves consistency and speeds up translation.
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What is a 'fuzzy match' with 75% similarity in a TM?
Fuzzy matches (typically 50-99% similarity) occur when the new text is similar but not identical to a TM segment. Translators receive the stored translation as a starting point and edit accordingly. Higher fuzzy match percentages mean less editing needed.
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What does 'the leverage reduces translation cost by 40%' mean?
Leverage analysis calculates the proportion of source content covered by TM matches (exact + fuzzy). High leverage reduces translation costs because translators charge less (or nothing) for content they only need to review rather than translate from scratch.
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What is a 'TM hit'?
A TM hit (or TM match) occurs when the current source segment matches a stored segment. Exact hits (100%) can often be accepted directly by the translator, while fuzzy hits require editing. More hits = faster, cheaper translation.
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Why is 'managing and cleaning TM' vocabulary important for a localization team?
A dirty TM can actively harm quality by suggesting outdated product names, wrong terminology, or incorrect translations. Regular TM maintenance — auditing, correcting, and removing problematic segments — is essential to maintain the value of the TM asset.
6 / 15
Reviewer: 'The TM hit rate for the UI strings is only 62%. We need to investigate why so many are not being matched.'
What does this comment primarily indicate about the Translation Memory (TM)?
This comment focuses on the 'hit rate,' which measures how often a TM segment matches a new one. A low hit rate (62%) suggests that the TM's similarity algorithm isn't accurately identifying matching segments, likely due to variations in wording or terminology. The reviewer is suggesting optimization of the TM's matching criteria rather than simply stating the content is poorly translated.
7 / 15
Slack Message from Alex (Localization Engineer): 'Just ran a TM clean on the 'User Profile' strings. Removed all segments with >90% similarity to existing translations and flagged those below 70%. We're aiming for high precision, not just recall.'
What is Alex primarily discussing when referring to 'segments with >90% similarity'?
Alex's emphasis on 'precision' and removing segments with high similarity highlights the risk of subtle changes in wording. Segments with >90% similarity are likely very close in meaning—altering them could introduce unintended consequences or inconsistencies into the translated output. The goal is to avoid these potential issues, even if it means slightly less recall (finding all possible matches).
8 / 15
PR Description for a new feature: 'Implemented API endpoint /user/profile. Leveraging TM data to pre-populate user profile fields with previously translated values where available, estimated cost reduction of 25%.'
What does 'leveraging TM data' in this context mean?
This description indicates that the API is using the TM's matching algorithm to find similar segments. It's not simply copying strings; instead, it's utilizing the TM's database of translations to suggest and potentially pre-populate fields with the most relevant translated values based on semantic similarity. This reduces the need for manual translation.
9 / 15
Standup Update from Ben (Developer): 'I've been working with the TM to translate the new onboarding flow. We're seeing a lot of 'TM hits,' which is great – it's saving us time, but we need to ensure the translations are still accurate and reflect the updated UI.'
What does Ben mean by 'TM hits'?
A 'TM hit' represents a successful match between a new string and an existing translated segment within the TM. It signifies that the TM's similarity algorithm has identified segments that are closely enough to reuse without significant modification, leading to increased efficiency in the translation process. Ben's caveat about accuracy highlights the importance of verifying these matches.
10 / 15
Code Review Comment from Sarah (Senior Developer): 'Consider adding a TM entry for 'customer support' – it's a frequently used term and should be included in the TM to improve hit rates.'
Why is Sarah recommending this action concerning the Translation Memory (TM)?
Sarah's recommendation directly addresses the goal of increasing 'hit rates.' By adding frequently used terms like 'customer support' to the TM, the likelihood increases that future content will contain these phrases and therefore be matched with existing translations. This is a fundamental principle behind effective TM usage: maximizing the number of matching segments.
11 / 15
Reviewer: 'The TM hit rate for the UI strings is only 62%. We need to investigate why so many are not being matched.'
What does this comment primarily indicate about the Translation Memory (TM)?
This comment focuses on the 'hit rate,' which measures how often a TM segment matches a new one. A low hit rate (62%) suggests that the TM's similarity algorithm isn't accurately identifying matching segments, likely due to variations in wording or terminology. The reviewer is suggesting optimization of the TM's matching criteria rather than simply stating the content is poorly translated.
12 / 15
Slack Message from Alex (Localization Engineer): 'Just ran a TM clean on the 'User Profile' strings. Removed all segments with >90% similarity to existing translations and flagged those below 70%. We're aiming for high precision, not just recall.'
What is Alex primarily discussing when referring to 'segments with >90% similarity'?
Alex's emphasis on 'precision' and removing segments with high similarity highlights the risk of subtle changes in wording. Segments with >90% similarity are likely very close in meaning—altering them could introduce unintended consequences or inconsistencies into the translated output. The goal is to avoid these potential issues, even if it means slightly less recall (finding all possible matches).
13 / 15
PR Description for a new feature: 'Implemented API endpoint /user/profile. Leveraging TM data to pre-populate user profile fields with previously translated values where available, estimated cost reduction of 25%.'
What does 'leveraging TM data' in this context mean?
This description indicates that the API is using the TM's matching algorithm to find similar segments. It's not simply copying strings; instead, it's utilizing the TM's database of translations to suggest and potentially pre-populate fields with the most relevant translated values based on semantic similarity. This reduces the need for manual translation.
14 / 15
Standup Update from Ben (Developer): 'I've been working with the TM to translate the new onboarding flow. We're seeing a lot of 'TM hits,' which is great – it's saving us time, but we need to ensure the translations are still accurate and reflect the updated UI.'
What does Ben mean by 'TM hits'?
A 'TM hit' represents a successful match between a new string and an existing translated segment within the TM. It signifies that the TM's similarity algorithm has identified segments that are closely enough to reuse without significant modification, leading to increased efficiency in the translation process. Ben's caveat about accuracy highlights the importance of verifying these matches.
15 / 15
Code Review Comment from Sarah (Senior Developer): 'Consider adding a TM entry for 'customer support' – it's a frequently used term and should be included in the TM to improve hit rates.'
Why is Sarah recommending this action concerning the Translation Memory (TM)?
Sarah's recommendation directly addresses the goal of increasing 'hit rates.' By adding frequently used terms like 'customer support' to the TM, the likelihood increases that future content will contain these phrases and therefore be matched with existing translations. This is a fundamental principle behind effective TM usage: maximizing the number of matching segments.
What will I practise in "Translation Memory Vocabulary"?
Practice English vocabulary for translation memory (TM): stored segments, fuzzy matches, leverage, TM hits, and maintaining clean translation memories.
How many exercises are in this module?
This module has 15 multiple-choice exercises, each with instant feedback and a full explanation of the correct answer.
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Where can I find more i18n & l10n exercises?
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How is this different from reading an article on the same topic?
Articles explain vocabulary and concepts in prose; this exercise tests and reinforces that vocabulary through active recall with immediate feedback — the two work best together.
Who writes these exercises?
Every exercise is written by the CoderSlingo team, drawing on real workplace English used in IT roles, then reviewed for accuracy and clarity.