Machine translation (MT) can rapidly generate draft translations, but it still falls short of perfect accuracy. In fact, many professional linguists report that raw MT output is often poor: for example, over 60% of surveyed translators agreed that most machine translations are “poor-quality” without human review (localizejs.com). That’s why MT is typically followed by post-editing and a final quality assurance (QA) step. In post-editing, a human linguist corrects obvious errors and adapts the tone and style. A subsequent QA pass — often by a second reviewer or specialized tool — checks the edited translation against all requirements. This extra layer of review catches mistakes (mistranslations, formatting bugs, style mismatches, etc.) before content goes live, protecting your brand and customer experience (localizejs.com) (crowdin.com).
The MTPE Workflow and the Role of QA
In a streamlined MT post-editing (MTPE) workflow, the process typically follows these phases:
Machine Translation: An MT engine (e.g. Google, DeepL, or a custom model) automatically translates the source text into the target language.
Post-Editing: A professional translator reviews the MT output. They correct errors, improve grammar, and adjust phrasing to ensure the text is accurate and fluent. The post-editor also matches the brand voice and target audience, making the translation feel “natural” (localizejs.com). Light post-editing fixes only glaring mistakes (typos, obvious mistranslations), while full post-editing refines style, tone, and terminology in detail (smartling.com).
Quality Assurance (QA): After post-editing, a final QA step validates the translation against project requirements (polilingua.com). This can be done by a second linguist (often called an LQA reviewer) or via automated QA checks in a translation management system. The QA reviewer scans for any overlooked errors or unintended changes introduced during editingphrase.com, and ensures the translation meets company style guides and formatting standards.
In practice, QA might involve sampling translated segments, flagging issues, and pushing corrections back into the project (smartling.com). Translation platforms often include QA tools or suites to streamline this step. For example, Smartling’s “LQA Suite” lets users snapshot translations, review samples for errors, and seamlessly apply fixes (smartling.com). The key point is that QA comes after post-editing: it’s a safety net that catches anything remaining, from small typos to larger consistency or context errors (polilingua.com) (phrase.com).
Common Errors Caught by Human QA
Human QA is essential because machine-assisted translations can miss a wide range of issues. Some of the most common categories of errors caught by QA include:
Mistranslations and Meaning Errors: Machine translation sometimes omits or adds words, misinterprets negations, or produces literal renderings that distort the original meaning (centus.com). A QA reviewer will spot if a sentence no longer conveys the intended message. For example, MT might translate an idiom too literally or confuse homonyms. QA ensures the translation accurately preserves the source meaning and fixes any mistranslations.
Tone and Style Mismatches: Each brand and audience has a desired tone (formal, friendly, technical, casual, etc.). MT output often defaults to a neutral or inconsistent tone. QA reviewers check that the voice matches the brand’s guidelines and the context. For instance, marketing copy should sound engaging, while a legal text must sound precise. The reviewer ensures wording and register fit the target audience (localizejs.com) (localizejs.com). A formal document mistranslated into an overly casual tone would be caught here.
Terminology and Consistency Issues: QA also enforces consistent use of terminology and style. Translators rely on glossaries and translation memories, but errors can slip through. QA finds places where the wrong technical term or product name was used, or where phrasing shifts unexpectedly. This includes checking adherence to company glossaries or style guides (e.g. always calling a feature “Knowledge Base” rather than sometimes “Help Center”). Consistency boosts professionalism; human QA ensures it.
Grammar and Fluency Mistakes: Even with post-editing, minor grammar, syntax, or punctuation errors can remain. The QA pass catches leftover mistakes (subject-verb agreement, plural forms, typos, misplaced commas, etc.) that automated tools missed. For example, a QA reviewer might notice a missing article (“the” or “a”), an extra space, or a misplaced quotation mark. These small issues can undermine credibility, so QA fixes them before publication (centus.com) (localizejs.com).
Context and Cultural Errors: Machine translation doesn’t truly understand context or culture. QA reviews can catch subtle errors like culturally inappropriate word choices, literal translations of idioms, or missing context. For example, an MT might render “be a peach” (an idiom) word-for-word; a human QA would correct it to the appropriate local equivalent. Context failures (e.g. confusing words that had different meanings in the source) are flagged and fixed.
Formatting and Technical Issues: MT can break formatting. For instance, untranslated placeholders (
%s,{0}, HTML tags) might be left in the text, or spacing around punctuation can be wrong. QA tools specifically check for these issues. Automated QA checks can flag missing commas, extra spaces, inconsistent punctuation, broken code snippets or UI labels (crowdin.com). A human QA reviewer ensures the target text’s formatting matches the source so it fits into the product UI or document layout properly. For example, a QA check would catch an untranslated software label or a date formatted incorrectly for the locale, preventing user confusion (crowdin.com).
In short, human QA catches what machines (and even careful post-editors) can miss: misinterpreted phrases, off-tone language, skipped terms, and any glitches introduced during editing. Including this step significantly reduces the risk of embarrassing mistakes reaching your customers (crowdin.com).
Practical Tips: Balancing Speed, Cost, and Quality
Every project needs a balance between turnaround time, budget, and final quality. Here are some practical tips to make MTPE plus QA work effectively:
Prioritize Content by Impact: Not all text needs the same level of scrutiny. Reserve full post-editing + QA for high-impact, customer-facing content (marketing pages, legal terms, user interface labels) where errors hurt brand image. For internal or low-risk content (internal docs, emails, draft posts), a lighter post-edit with spot checks might suffice (smartling.com). In other words, use your resources where they matter most to the business.
Pre-Edit Source Text: A “tidy” source improves MT output. Write clear, concise sentences with consistent terminology and minimal idioms. Avoid complex phrasing (keep sentences <20 words where possible) (phrase.com). Pre-cleaning the source (fixing typos, splitting run-on sentences, unifying term usage) gives the MT engine better input, so the draft requires less editing and QA. In practice, the cleaner your source, the faster and cheaper the post-editing and QA will be (phrase.com).
Leverage Automation: Use QA tools to catch simple errors quickly. Modern translation platforms offer built-in QA checks for punctuation, placeholders, terminology, and formatting. For example, a QA tool will highlight a missing comma or a variable (
{username}) that was accidentally altered (crowdin.com). This lets linguists focus on nuanced fixes. Automated QA also ensures consistency across the project (e.g. it will flag every instance of an inconsistent term). Integrating such tools means fewer errors slip through and reduces manual checking time (phrase.com) (crowdin.com).Maintain Glossaries and Style Guides: Before translation begins, provide translators and QA reviewers with a glossary and style guide. Define your brand voice, preferred terms, and any strict rules (e.g. you always say “Cancel Subscription” instead of “Stop Subscription”). A shared glossary helps MT engines (if custom) and human editors use the right words. A style guide ensures consistent tone (friendly vs. formal) across all text (localizejs.com) (localizejs.com). The less guesswork for the linguists, the fewer corrections needed later.
Iterate and Learn: Track the types of errors caught by QA and feed that back into the process. For example, if QA repeatedly finds that MT mis-translates a particular technical phrase, you might add it to the translation memory or glossary, or adjust the MT engine’s training. Likewise, if a certain style issue recurs, update your guidelines. Over time, these improvements reduce post-editing and QA effort, accelerating future projects.
Sample Wisely: If time or budget is tight, you can sample-check only a portion of the translation. But choose strategic samples (high-visibility sections or randomized segments) to ensure overall quality. Any errors found can hint at systemic issues to fix. This “risk-based QA” approach can save time while still protecting brand-critical content.
By combining machine speed with targeted human review, you achieve the best of both worlds. Human QA doesn’t negate cost-savings from MT; it maximizes value by applying human insight where it counts. As one expert note suggests, automating repetitive translation tasks with MT and “reserving human expertise for high-value or creative content” helps balance cost, speed, and quality (kantanai.io). In practice, that might mean funneling bulk informational text through a fast MTPE pipeline, while dedicating extra QA time to product descriptions or legal pages where every word matters.
Business Impact: Quality Translations and Brand Reputation
Investing in human QA has clear business benefits. High-quality, error-free translations improve customer experience, build trust, and protect your brand image. Studies show that consumers “value translations that accurately convey the meaning… ensuring cultural sensitivity and natural-sounding language,” and that they appreciate when translations are free of mistakes and inconsistent terminology (unbabel.com). In contrast, even small translation errors can confuse or frustrate users. For example, a misplaced comma or a wrong button label in a user interface can lead to user errors or support calls. On a larger scale, poor translations can lead to abandoned purchases, negative reviews, or legal issues.
Multiple sources warn that bad localization directly harms reputation and revenue. Crowdin notes that “low-quality translations can negatively impact your relationships with clients and your company’s reputation” (crowdin.com). Unbabel similarly points out that translation mistakes “impede the customer experience” and “lead to frustration, potentially damaging your brand’s reputation” (unbabel.com). In other words, skimping on QA may save a bit in translation costs up front, but a translation error seen by customers can cost far more in lost sales or brand damage.
Conversely, prioritizing translation quality (including thorough QA) can pay dividends. One real-world example: fintech company GoCardless used high-quality translations to expand its help center dramatically. By carefully translating and QA-reviewing support articles, they grew from 11 original articles to over 900 multilingual articles, freeing up support teams and enabling service in new countries (unbabel.com). This highlights how quality localization — not just raw speed — can enable global growth. Good QA means fewer customer misunderstandings, fewer support tickets, and more scalable self-service. All of these improve customer satisfaction and loyalty, which ultimately boosts revenue.
In summary, adding a human QA step to your MTPE workflow means protecting your brand and your bottom line. It ensures that your content not only reaches new audiences quickly, but also conveys the right message in the right way. By catching errors and enforcing consistency, QA upholds the professionalism and credibility of your localized content. That’s why even in a fast-moving MT-driven process, a final human quality check is often well worth the investment (crowdin.com) (unbabel.com).
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See our previous blog post on “Indonesian Words Beyond the Bounds of English Translation | Part 2″
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