Google Translate, a ubiquitous tool in today's globalised world, boasts an impressive feat – translating between 133 languages.
But with such a vast scope, the question arises: how accurate is Google Translate really? Can it be relied upon for accurate and nuanced translations in various contexts?
Let's delve into the data to uncover the truth.
The answer, like many things, is nuanced. Studies reveal that Google Translates accuracy fluctuates significantly depending on the language pair. For commonly used languages like English and Spanish, the accuracy can be remarkably high.
A 2021 UCLA Medical Center study found that Google Translate preserved the overall meaning in 82.5% of English-Spanish translations.
However, the same study also found a wider accuracy range of 55% to 94% across all language pairs. This disparity highlights the challenges Google Translate faces with less common languages.
The availability of training data plays a crucial role – languages with a smaller digital footprint often have lower translation accuracy because there is a flood of bad machine translations that has serious impact on AI training models.
In certain contexts, relying on Google Translate may not be advisable due to concerns about accuracy, effectiveness, and privacy.
The following are scenarios where caution should be exercised:
It is essential to understand the limitations and potential risks associated with relying solely on machine translation, especially in contexts where precision and clarity are critical.
While Google Translate may suffice for simple messages with low accuracy expectations, it's crucial to prioritise accuracy and clarity, especially in contexts where misunderstandings could have significant consequences.
When it comes to translating and localising content, investing in expert human linguists with industry-specific credentials is a significant expense for businesses. However, these high-quality translations are ideal datasets for training machine learning models to power AI engines specific to your company, resulting in improved results.
Creating clean datasets is the perfect way to future-proof your translations because it gives you a return on investment, saving time and money overall. Why keep translating the same content when a private AI translation engine can do it for you?
Guildhawk has focused on future-proofing translated content since its establishment in 2001. Our partners appreciate receiving incredibly accurate translations but do not want to continue translating the same content each year.
That is why we began training machine learning models with high-quality translated data that professional linguists have rigorously vetted.
This approach powers our AI-translation GAI platform, and our partners now request that we build translation engines specific to their businesses to ensure quality and accuracy. Our training strategy for GAI relies solely on using data vetted by professional linguists.