Machine Learning in Localization: Why it Matters

Written by

Argos Multilingual

Published on

30 Nov 2021

Not long ago, the notion of a machine that could understand spoken words and translate them to a target language seemed like something from the fevered imagination of a science fiction writer. Fast forward to late 2021, and artificial intelligence (AI) and its subset machine learning are causing a revolution in localization.

It’s useful to explain the differences between AI and machine learning, as the two terms are commonly (and incorrectly) used interchangeably. Put simply, AI is a bigger concept dealing with the creation of intelligent machines that can simulate human thinking capability and behavior, whereas machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.

AI and machine learning have long been back-engine contributors to language services processing in functions like text-to-speech, but the past few years have seen massive improvements in the way that machine learning platforms handle language-related tasks. This is largely due to developments such as an unprecedented increase in the amount of accessible global data and the rise of neural machine translation (an end-to-end learning approach for automated translation with the potential to overcome many of the weaknesses of conventional phrase-based translation systems). Let’s take a quick look at a few ways machine learning is shaking up the localization process.

Authenticity and immediacy

It’s not enough to simply know the rules of a language – translators also need to be well versed in the culture and habits of the people who speak it. This can be a real challenge when cultural and linguistic norms are constantly shifting.

Machine learning can track the evolution of language and identify when a translated word is outdated or doesn’t make sense. It’s perfect for handling vernacular content such as user-generated text, which is less structured than formal prose. It can also pick out phrases, idioms, and sayings specific to a particular language, a task that even the best human translators often find challenging.

Speed and efficiency

Machine learning has proven to be an ideal way to significantly reduce the time it takes to localize content effectively, allowing companies to translate more words per day and deliver translated content to customers faster than ever before.

If an application or website needs to be localized for multiple locations, machine learning can track the most recent and granular changes in languages. This means that less time needs to be spent by human editors. In addition, content created in a content management system allows high-quality translated content to be saved and reused for future projects, dramatically increasing the value of machine learning-based solutions.

Quality and accuracy

Any casual user of tools like Google Translate is aware that the quality of machine learning-assisted translation has improved exponentially in recent years. The advanced tools in this space leverage natural language processing (NLP). NLP is a subfield of artificial intelligence that helps machines understand natural human language by bringing context and grammar to translated phrases. The level of accuracy depends largely on the source and type of the content.

Machine learning will continue to improve over time through better neural network architecture, vetted quality data, and more computation. These changes in neural AI technology will require human translators to adapt to the benefits of the technology and focus on what humans are good at.

That’s why anyone concerned that machine translation will kill jobs should be aware that the human component of language services has never been more important. Talented employees will be needed for the foreseeable future to train machine learning solutions on the basics of reading and comprehension while also providing the crucial quality control role, reviewing and modifying machine translations.

The Argos way

Wondering if MT is right for your translation and localization projects? We can take the guesswork out of the process. Our in-house team of experts knows what to do and has the tools and infrastructure in place to help you succeed with MT. To find out more, get in touch with us.