Translation memory

Set up translation memories

Setting up translation memories | Smartcat Help Center Translation memories (TMs) are the single most important linguistic asset to optimize your translation performance. They improve quality and consistency, reduce project turnaround times, and decrease the number of words to translate by pre-populating new translations with previously translated content that matches current content for translation. For these reasons, it's crucial that they are set up properly when you create an account on Smartcat. In addition to enhancing project workflow, correct creation of TMs also averts the possibility of missed word and phrase matches, which would mean higher translation costs. Essential information on Smartcat translation memories Here are some essential need-to-know facts about TMs in Smartcat. Limitless TM creationIn Smartcat, you can create as many TMs as you like. For instance, you may wish to have a different TM for each specific subject matter focus for your content. As an example, a corporate legal department might have one TM for product terms and conditions-related content and another for employee contracts. Limitless data storageThere are also no limits as to the amount of data that you can store in your TM databases in your Smartcat account. You can organize TMs using client and project group labels. TMs can be single-language or multilingualAs well as the standard one source and one target language form of TM, Smartcat also enables you to create multilingual translation memories. This means that you can have one source language and as many target languages as you want. This helps reduce the number of TMs that you would need to create if you could only use single-language TMs, helping with organization and workflow management. How to create translation memories in Smartcat Creating a new TM in Smartcat is simple. Step 1Scroll down and click on Linguistic Assets via your Smartcat workspace home page. Step 2Click Create TM. Clicking Create TM will generate the following dialogue box.Note: the numbers have been superimposed to provide instructions below Field 1: TMX, SDLTM OR XLSX fileImport a TM file in one of the available formats. Field 2: NameAssign a unique name. In many cases, it is recommended to choose a name based on the customer name to simplify data management. Fields 3 and 4: Source and target languagesChoose the source language (3) and all the target languages (4). There can be only one source language but you can choose as many target languages as needed for a specific client. In most scenarios, matches are found based on comparing new sentences with sentences stored as the source language but Smartcat now allows translation memories to be reversed automatically when used as reference (in read-only mode) and matches can be found in the target language in this case. Fields 5 and 6Labels can be assigned for a client (5) and project tag (6). Field 7: SubjectThere is an option to define a subject (7) for the translation memory but this option is generally redundant if the translation memory is assigned to a specific client. It could be useful when dealing with clients who work across multiple fields and separate translation memories need to be maintained. Field 8: CommentsYou can also add comments or a description (8) for each translation memory. Click Save when you are done. That's it! With this brief article, you should now know how to correctly create a TM in Smartcat, with one or more target languages.

Organize your translation resources

Organizing resources | Smartcat Help Center Smartcat offers numerous translation resources, or, linguistic assets, to help ensure quality and consistency in your translations. Translation memories Smartcat supports multilingual translation memories, which makes creating and managing translation memories easy! To create a translation memory, you need to follow these steps:Click on Linguistic Assets from your Smartcat workspace: 2. Make sure you have chosen Translation Memories from the drop-down menu: 3. Select “Create TM.” Quick note : One of the less obvious advantages of multilingual TMs is that you can create a new TM where the source language is one of the target languages of the original TM. This can be convenient if you work in mixed language pairs. 4. Fill in the fields: 5. You can upload external translation memories in the following file formats: TMX, SDLTM or XLSX file. Or, you can also add new terms one-by-one, or as you go along. Once you have created several TMs, your list might look like this: Glossaries You can now use the same approach to organize your terminology databases, which are called glossaries in Smartcat. To do this, go to Linguistic Assets → Glossaries. You can create a glossary using the same client and project group labels: Here we have replicated the same structure as the one for translation memories. Just like TMs, glossaries are multilingual in Smartcat. Unlike TMs, though, they don’t have a strictly set source language — you can use a glossary in projects where any two of its languages are present as the source or the target. How detailed should you go? With both TMs and glossaries, you can go with a high level organization structure with one resource per customer, or do something similar to what we described above. Our suggestion is to mix both on a case by case basis:For clients with a complex corporate structure, it is a good idea to match that structure with the resources.For smaller clients, a single terminology database will take less time to configure and will be easier to maintain. If you want to go hardcore, you can create a new TM for every project, while making sure to properly choose the client and project group for each. Smartcat will still fetch these “micro-resources” for subsequent projects, as described in the next section. Note: While creating a new TM with each project might help with data segregation, it might also create a lot of TM duplication that could reduce translator productivity. Putting it all to work Now, whenever you create a project and choose a client/project group, Smartcat will automatically fetch the translation memories and glossaries associated with them: This ensures that you leverage every possible resource related to said client and project group, eliminates many potential project creation errors that lead to unnecessary work, and just saves time. Takeaway Organizing your data properly from the get-go increases the productivity of your project managers, who will no longer spend time looking for matching resources. This will also make things easier for your translation team, who will benefit from optimized TM leveraging and consistent terminology. Ultimately, this will increase your translation throughput, profit, and quality alike. This article was created in partnership with Braahmam .

How do I connect my existing translation memory or glossary?

How do I connect my existing translation memory or glossary? If you already have a translation memory (TM) or glossary you want to use in Smartcat, you can connect it to your projects in just a few steps. The process depends on where your linguistic assets currently live. Scenario 1: Your TM or glossary is already in Smartcat If you've previously created or imported a translation memory or glossary into your Smartcat workspace, you can attach it to any project. To attach an existing TM or glossary to a project: Open your project and go to the project Overview page.Click on Linguistic Assets in the project settings panel.Click Add, then select Select an existing TM (for translation memories) or Select an existing glossary (for glossaries).Choose the asset(s) you want to attach from the list and click Add. That's it! Your existing linguistic assets are now connected to the project and is used during translation. 📌 You can use the search and filter options to find assets by subject, client, or project tag. Scenario 2: Your TM or glossary is in an external tool If your translation memory or glossary was created in another tool (such as SDL Trados, memoQ, or a spreadsheet), you'll need to import it into Smartcat first, then attach it to your project. Step 1: Import your asset into Smartcat For translation memories: Smartcat accepts TMX, SDL TM , and Excel (XLSX) filesSee: Import and export translation memories For glossaries: Smartcat accepts Excel (XLSX) and MultiTerm XML filesSee: Importing and exporting glossaries Step 2: Attach the imported asset to your project Once your TM or glossary is imported into Smartcat, follow the steps in Scenario 1 above to attach it to your project. Related articles Import and export translation memoriesImporting and exporting glossariesAdd a translation memory to a projectCreate a glossary

How TM matching works in Smartcat

How TM matching works in Smartcat Overview Translation Memory (TM) matching in Smartcat compares new source segments against your existing TM entries to find reusable translations. Match percentages indicate how closely a new segment matches stored entries, ranging from fuzzy matches (75-99%) to exact matches (100%) to context-verified matches (101-103%). When to use it Use TM matching when you want to: Leverage previous translations — Reuse work from past projects to save time and costMaintain consistency — Ensure the same source text gets the same translation across documentsSpeed up translation — Automatically insert high-confidence matches without manual workReduce costs — TM matches are priced the same as new AI translation and is typically less expensive than human translation and review Key concepts TermDefinitionFuzzy match (75-99%)Source text is similar but not identical to a TM entry. Requires translator review.100% matchSource text is identical to a TM entry, but surrounding context was not verified.101% matchSource text matches AND one adjacent segment (before or after) also matches the TM context.102% matchSource text matches AND both adjacent segments match the TM context.103% matchSource text matches AND the segment's key/ID matches (software localization files only).Context metadataInformation about surrounding segments stored with each TM entry to enable context matching. How it works Match percentage calculation When you open a document, Smartcat compares each source segment against your enabled TMs: Match TypeWhat it meansConfidence level75-99%Similar but not identical text. Differences may include word changes, additions, or deletions.Low — requires review100%Exact text match. The source is identical, but context wasn't verified.Medium — likely correct101%Exact match + one adjacent segment matches context stored in TM.High — context verified102%Exact match + both adjacent segments match context stored in TM.Very high — full context match103%Exact match + segment key/ID matches (software files only).Highest — key verified 💡 Tip : Review 100% matches carefully during translation — they may need adjustment for the specific context, while 101%+ matches provide additional confidence through context verification. How context matching works When Smartcat stores a segment in the TM, it also stores the content of the previous and following source segments as context metadata (x-context-pre and x-context-post). Example of what's stored in the TM: Previous segment: "I live in a small village."Source segment: "I have a small house." → Target: "J'ai une petite maison."Following segment: "It is blue." When the same segment appears in a new document: If neither adjacent segment matches → 100% matchIf one adjacent segment matches → 101% matchIf both adjacent segments match → 102% match Context matches provide higher confidence that the translation is correct for the specific location in the document. 💡 Tip : For maximum consistency, use TMs with context matches (101%+) as they provide the highest confidence that the translation is appropriate for the specific document location. How key ID matching works (103%) For many  files (JSON, XLIFF, RESX, etc.), segments often have unique identifiers or keys. Smartcat can use these keys as an additional context signal. When a document uses ContextId matching (determined by file format): A 103% match means the source text is identical AND the segment's key/ID matches the TM entryThis is the highest confidence match available ⚠️ Key ID matching (103%) is only available for file formats that contain segment identifiers. Standard document formats use previous/next context matching (max 102%). TM matching priority over AI translation Smartcat processes segments in this order: TM lookup first — Each segment is checked against your TMs for matchesAI translation second — Segments without TM matches (or below your threshold) go through AI translation By default, TM matches at 100% and above are confirmed automatically and do not require human review. This means: Exact TM matches are trusted and applied without additional processingAI translation only runs on segments that don't have sufficient TM coverage You can configure this behavior in translation rules to require different thresholds for auto-confirmation. Requirements and Limitations Requirements The TM must contain entries for the same language pair as your documentFor automatic translation to insert matches automatically, you must configure translation rules Limitations The default minimum match threshold is 75% — matches below this are not shown. You can lower the threshold to 50% in the translation memory settings for the project.103% matches are only available for file formats with segment keys (software localization files)Context matching requires the TM to have been populated with context metadata Configuring translation rules Step 1 — Open automatic translation settings In the left sidebar, click Translation rulesClick Add Rule → Translation Memories Step 2 — Configure settings for the translation rules Select which TM to use from your enabled TMsIn the Minimum match percentage field, specify the threshold for inserting matchesOptionally, set Minimum TM segment Quality to only use reviewed TM entriesOptionally, set Minimum word count in a segment to avoid inserting matches for very short segments Step 3 — Configure confirmation behavior In the Confirm segments field, specify whether to auto-confirm inserted translationsFor high-quality TMs with 100%+ matches, you can confirm at the translation stageFor lower thresholds or uncertain TM quality, leave segments unconfirmed for translator review 💡 Tip : Set up separate rules for each TM if you have multiple — rules execute in order, so put your most reliable TM first. Step 4 — Save and run Click Save & Run to apply the rules to all documents in the project. 💡 Tip : Use the "Pretranslate" button after configuring rules to apply TM matches to existing documents in your project. Troubleshooting TM matches aren't being applied to my project Check these common causes:Wrong language pair — Ensure the TM contains entries for your document's source and target languagesNo translation rules — TMs provide suggestions in the editor, but automatic insertion requires translation rulesThreshold too high — If your minimum match percentage is set to 100%, fuzzy matches won't be inserted. If your minimum TM segment Quality is too high, it may also prevent matches.TM is empty — Check that the TM actually contains entries (view TM contents in the TM management area) I see 100% matches but expected 101% or 102% Context matches require:The TM entries to have been created with context metadata (from a previous project with adjacent segments)The adjacent segments in your new document to match those stored in the TMIf you imported TM entries from an external file, context metadata may not have been included I don't see 103% matches for my software files 103% matches require:A file format that contains segment keys/IDs (JSON, XLIFF, RESX, etc.)The TM entries to have been created from the same or similar file with matching keysStandard document formats (DOCX, PDF, etc.) use previous/next context matching and max out at 102%

Manage linguistic resources in the Editor

Managing linguistic resources | Smartcat Help Center Smartcat includes a variety of tools like translation memories and glossaries that help you improve translation quality and consistency. Translation memory matches represent the segments that were previously translated (each time you set up a project you can assign a translation memory to it or it ill be created automatically) in one of your projects or taken from an imported translation memory linked to the project. Glossary matches represent words and phrases taken from a glossary linked to the project. Translation memory and glossary matches are displayed in the CAT Panel. Inserting translation memory and glossary matches Translations from the TM are sorted in the descending order of the match percentage. By default the system uses the translation with the highest match percentage. By you are free to make a different choice, go with AI translation results or correct the segment to your liking. To insert a TM match, press Ctrl+the number of the match in the list. You can also set up automated insertion of TM matches when creating a project. Glossary matches are displayed in the CAT panel along with the TM matches and are inserted in the same manner. The terms are also highlighted in yellow in the source text. Managing TM matches This option is only available for project managers or linguists assigned to the editing stage. All other users can view the TM match but not make changes to it. Clicking on the pencil icon or information icon (an “i” inside a circle) depending on the user role at the top-right corner of a TM match will open a dialog box, which allows users to either edit or remove the selected TM match. Managing glossary terms You can add terms into glossaries applied to the project either on the glossary page or directly in the Editor. Note, that if you are working on a project that a client has created in the system, you might not have the right to work with glossaries, but you can still suggest a term. In this case, the client will see the suggestion then add it to the glossary, edit, or reject it. To add or suggest a term, select it with your mouse and press Ctrl+E. Then fill in the required fields and press Add . The term will be added to the glossary and will then be available in the CAT panel. As opposed to translation memories where only one TM is selected for writing, it is possible to add (or suggest) terms to any of the glossaries associated with the project. Editing terms To edit a term, select it in the Editor panel, and click Edit in the CAT panel. Make changes you want and click Save. You can also work with terms on the glossary page. Click Go to term in the CAT panel. The glossary will open in the new browser tab.

Understanding word match levels in Smartcats CAT tool

Word match levels | Smartcat Help Center Learn the differences between word match levels in Smartcat's CAT tool, Smartcat Editor It can sometimes be confusing differentiating between the different level of word matches when using a computer-assisted-translation (CAT) tool like Smartcat Editor. In this article, let's look at these differences, explaining 100% matches compared to 101% and 102% matches, and also fuzzies and near matches. 100% and 101%/102%. What's the difference? 101/102% matches are called by different names, depending on the CAT tool. also referred to as context matches, perfect matches or ICE matches. When a segment is stored in a Smartcat translation memory, Smartcat stores not only the source and target text, but also the content of the previous and following source segment. For example, this is what you might see in the TM. <Previous Segment>  I live in a small village. <Source Segment> I have a small house. <Translated Segment> J'ai une petite maison. <Following Segment> It is blue. The translation is stored only for the segment that is being translated, but the other two segments are used to provide context. 100% matches explained If this same segment was encountered again, and neither of the two accompanying segments matched the TM-store, there would be a 100% match because only the text matches. 101% matches explained If in the next document, one of the context sentences was present, there would be a 101% match. 102% matches explained If both were present, it would be a 102% match. Having the context sentences match what is stored in the TM helps increase the certainty that the translation is a perfect match for new segment. In practice, 101/102% matches are often locked during pre-translation by project managers when the project is started because customers don't pay for these segments in most cases. Explaining nearly exact and fuzzy matches in Smartcat Let's look at the difference between nearly exact and fuzzy matches, as well as the different tiers of fuzzy matches. Nearly exact match (95%-99%)The source text in the segment is identical to the match, albeit with minor discrepancies in numbers, tags, punctuation marks, or spacing. In pre-translation, this represents a good match by default, though it can be customized. Fuzzy match (50%-94%)The source text closely resembles the source text in the match, yet some variations already exist in the text. When it comes to the required editing, three categories of fuzzy matches can be identified. High fuzzy (85-95%): For segments of average length or longer (typically 8-10 words or more), there is usually a discrepancy of just one word.Medium fuzzy (75-84%): In segments of average length or longer (8-10 words or more), typically there is a variation of two words.Low fuzzy (50%-74%): In segments of average length or longer (8-10 words or more), the difference encompasses more than two words. In pre-translation, the term "any match" encompasses all types of partial matches together, commencing at 50% by default, though this can also be adjusted to suit preferences.

Delete or overwrite a translation memory

Managing memory deletion or overwriting | Smartcat Help Center In this brief article, let's look at how to delete and overwrite translation memories (TMs). How to delete a translation memory If you don't need a TM, select it from your TM list and click Delete. Keep in mind that you can't delete a TM if it is still in use in any project. If such a TM has to be deleted, you may add another TM for the project or delete the whole project.Also, please note that a deleted TM cannot be restored. How to overwrite a translation memory If you realize that a TM contains erroneous information, you can overwrite the content with updated, correct, data. Option 1 If you already have another approved version of the TM in an existing file, you can use that file. Option 2 You can also download the TM in a TMX format and use a text editor to make corrections as needed. When you overwrite a translation memory, the Smartcat system removes all existing translation units from the TM. Only after this step does it then import the correct TMX, SDLTM, or XLSX file. Overwrite a TM in three steps Step 1 Select it from your TM list and click Overwrite TM Step 2 Click Add and select the file from your computer Step 3 Click Import Smartcat will process the file overwrite command and display messages to inform you of its progress. That's it! With this information, you should now know how to delete and overwrite your TMs in Smartcat.

Choose an translation engine

MT engine selection | Smartcat Help Center Smartcat has eight industry-leading translation engines that are used to instantly translations, whether that be for files, websites, software, designs, videos – anything you need translated can first be pre-translated with high accuracy. The machine translation engines are: Google Statistical translation engineGoogle Neural translation engineMicrosoft Translator - This includes statistical and neural engines depending on the language pair.Yandex translation engineBaidu Translate APIDeepLAmazon TranslateModernMT Translation engine Intelligent routing analyzes your text and selects the best translation engine for the specific language pair. When you translate a document or create a translation project, you can enable intelligent routing or select translation engine (available for Unite subscribers and higher). Watch the video or read through the steps as described below the video: When translating a document: click on the Advanced settings when creating translation and select the desired Provider for machine translation in the window that opens. Press Apply now. When creating a translation project: open the Linguistic assets list from your account homepage or from the projects Overview page, click on the gear icon in the machine translation section and adjust the settings in the window that opens. Press Save&Run. 3. It is possible to select a different engine for each language. By clicking Add option, you can add languages to a specific engine. Each engine supports a specific number of languages. So some translation engines may become unavailable if there is no coverage from these engines. Backup machine translation engine We also have a feature that greatly improves the pre-translation performance! If the default machine translation engine provides an empty or broken result, meaning there is a critical error show in the Smartcat Editor, the platform will automatically fall back to its second machine translation engine option, that being Google Neural Machine Translation (NMT). As such, you won't have to worry about errors (or rather, this will decrease significantly). FAQ Which translation engine is best for my projects? There is no good answer to this question as the final choice of an translation engine might come down to many possible factor. For example, some translation engines produce better results for a specific language pair or if equally capable, results might be affected by the topic. Some companies publish some analysis of AI output and rank engines for some language pairs. One such company is inten.to, and they post some results on a regular basis. The latest study is available here.Studies like this one might give some insights into what engine is better for some language pairs, but when dealing with a large project, users should perform some testing with their translation teams and collect some feedback. The perception from translators might vary from the automated results generated for the studies. Testing a couple of thousand words with selected engines should be sufficient in most cases. I already have an account with Google/Microsoft. Can I use it with Smartcat? If you have accounts for the custom Microsoft and Google translation engines you can connect them to Smartcat.To do so you need to provide your credentials in the Workspace settings section and contact our support team.Once the accounts are connected, the corresponding AI engines will be available for use among the rest of Smartcat translation engines. The words translated using these engines will be deducted from your Smartwords balance, as per usual.  What machine translation engines are integrated with Smartcat? The following engines are integrated with Smartcat.Google Statistical translation engineGoogle Neural translation engineMicrosoft Translator - This includes statistical and neural engines depending on the language pair.Yandex translation engineBaidu Translate APIDeepLAmazon TranslateModernMT translation engineTo learn more about selecting a translation engine, refer to this article. 

Understand glossaries and translation memories

Translation memories, glossaries | Smartcat Help Center Critical localization projects, especially the more technical, require extra attention to terminology and phrasing to ensure consistency. That’s why we let our users create and use translation memories and glossaries. Translation memories (TMs) are databases of previously translated sentences, usually in CAT tools, and glossaries are databases of set terms. You can use them as translation references for your projects and save time and money on editing and keep translation quality standards high. Glossaries are organized collections of approved translations for specific terms. These can be technical terms, industry-specific jargon, or just set words that are used frequently in your content. While you can use TMs to search for previous translations of a given term, glossaries provide a much more structured and organized interface, making them easier to use and maintain. How do translation memories work? Each time you edit and confirm a segment in the Editor it’s saved in Smartcat’s internal database for further use. After translating a segment, you can save it as a translation memory.  Translation memories automatically retrieve and suggest previously translated text when the technology detects identical sentences or similar fragments of text. If the segment matches a translation memory in the project, it is recorded as a 102%. When you get a suggestion from the translation memory, you can either accept the proposed translation, edit it, or ignore the suggestion and translate the segment from scratch. How do translation memories help you? Saving time. The more content that is already translated, the less work the translator and the editor have to do.Improving quality. Translations are more consistent in terms of terminology and style.Cutting costs. The less work involved in the translation, the less you’ll have to pay translators and editors. In addition, Smartcat offers special rates for TM matches.  If we take a document containing 31 words, where 14 words are new, 12 words are fuzzy matches, and 7 words are repetitions, this means you’ll save almost 40% on translation costs. The calculation looks like this: (14 × 1) + (12 × 0,4) + (7 × 0) = 18.8. Translation memory settings while creating a project https://help.smartcat.com/adding-translation-memory-project/ Importing translation memory https://help.smartcat.com/1539635-importing-exporting-translation-memories/ Deleting translation memory https://help.smartcat.com/1539671-deleting-or-overwriting-a-translation-memory/ How do glossaries work? After you create or import a glossary you can associate it with a specific project. After, when a glossary term is detected in the source text, the system will automatically offer the stored translations for the term. You can accept or decline the word or phrase suggestion. How do glossaries help you? Diversity. You can have the same term translated differently for different clients as it's stored in different glossaries. Easier collaboration. Your translators always have enough context even if they have to switch between multiple projects. Speed and quality. Glossaries help to ensure consistency the same way as translation memories do.