Machine learning and professional translation: a successful pairing

Machine learning
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Machine learning has become essential for digitalization and in order to face up to a new phase in various market niches. Want to discover how its application affects the translation sector?

What makes the support of a translator essential for machine learning?

You’re bound to have heard that machine learning makes it possible to automate some specific tasks, such as translation, for example. A great example of this is the well-known Google Translate, which now interprets the sentence to be translated as a whole, in order to offer the most reliable results. Even so, it still lacks two key aspects that only a professional translator can offer: an understanding of the entire text and analysis of the elements that may alter the actual meaning of the sentence or text (irony, double entendre, etc.).

In other words, the automatic system is more effective for the translation of a single word or a street sign, but will not offer a professional translation. Curiously, as they are aware of the potential problems of their use, automatic-translation programs include the option to evaluate the result obtained in order to continue improving the system – though there are still some gaps that will be difficult to fill with any algorithm or new program.

Challenges faced by translators

The forecasts are not at all promising. It is estimated that, within a few years, 50% of translations made across the world will be done for free – resulting in the loss of thousands of jobs. Some of the most significant challenges faced by translators today include:

· Demonstrating that the way in which automatic-translation tools decipher patterns and store information is not synonymous with a successful translation.

· Specifying that words do not maintain a mathematical relationship based on the calculation of probabilities, as indicated by the creators of these programs. It’s essential that we continue to value the freedom of authors when it comes to drafting a text.

· Learning not to see machine translation as an enemy, but as a tool that can help us – though it offers a result that must be complemented with the professional experience of a translator.

Without a doubt, both of these two aspects of the process feed back into each other. Improving translation programs can save professionals time, while programmers also need experts in the field to continue improving this software that has threatened the job stability of translators for years, without ever impacting this to the extent once feared.

As a result, machine learning has come to help us improve translations – however, it does not have the necessary capacity to assess the nuances of each sentence. The goal is simply to continue specializing, training and adapting to new market needs. It’s always a good idea to anticipate any possible advances in translation programs. In the meantime, don’t forget that if you want to achieve optimal results, all you need to do is get in touch with our translation agency. We can’t wait to hear from you!

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