Machine Translations: Understanding the Technology

In today’s interconnected world, there is a growing demand for translation services, translation tools, and translation devices. We are now facing a new era where the massive demand for translated content can be handled only with the help of machines. From companies through travelers, to students, translations are used to facilitate communication and are birding linguistic barriers more than ever before. In the following lines, we will look at the concept of machine translation (MT) and the technology behind it. We will also discuss how machine translations have transformed translation processes.

Translation technology has actually been around for more than 50 years. Yet, with the increasing globalization, it is only natural that it continues to grow and become more essential to communication between people than ever before.

Back in the day translation was done manually with the sole use of a dictionary and one’s best judgment. With the introduction of translation technology, however, this approach was changed forever. Various tools were created with the idea to facilitate the translation processes and increase their accuracy. Up to the point where we have come today.  

The use of computers translating text is something that we are already used to. How easy it is for us to put a foreign word into a translator, and with just one click, we already know its meaning. But have you ever asked yourself what is the science behind it?

One of the translation technologies that is widely used by companies and organizations all over the world is machine translation (MT). It involves computers that are programmed to translate text into other languages with minimal to no human intervention.

As a result, it is now possible for us to translate large volumes of content much faster, and much cheaper. The quality of machine translation is also not to be underestimated thanks to advancements in natural language processing and machine learning algorithms. What is more, MT software can be customized to fit specific industries, niches, and even individual users’ needs. Although machine translations not yet entirely replace humans, they are still offering good enough translation results. Considering all of this together, we can say that machine translation has fundamentally transformed the translation process as we know it.

What makes MT so popular recently are the advances in technology that have taken place and the way machine translation has evolved. So, let’s take a closer look at how exactly it all works together.

To better understand machine translation, it is important that we look at the science behind it. Simply put, machine translation is the process of automatically translating text from one language to another without the interaction of a human.  

If we look at it in detail, the process is actually complex as it involves the use of algorithms and models that analyze and understand human language to generate adequate translations. Modern machine translation is much more advanced than its ancestors in that it actually analyzes all text elements and recognizes how the words influence each other in order to make a meaning.

Over the years, the development of MT has undergone some significant changes bringing to the surface several types of machine translation systems. Here are the four main types of machine translation that are most commonly used:

• Rule-based machine translation (RBMT)

These systems rely on a set of rules and dictionaries to translate text. These rules are typically created by linguists or language experts and are based on the structure and rules of the source and target languages. While RBMT systems are highly accurate, they still require a lot of manual work that is needed for the creation of the rules. What is more, these systems can be tailored to a specific industry or topic. Yet, they might not be the best option for translating informal or conversational texts.

• Statistical machine translation (SMT)

SMT systems are using statistical models to identify the most likely translation of a given sentence or phrase. This is possible thanks to the use of machine learning algorithms that analyze large amounts of parallel text that already exists. The software then makes intelligent predictions on the basis of statistical patterns. Compared to RBMT systems, SMT systems can be trained relatively quickly.

• Neural machine translation (NMT)

Neural machine translation systems are perhaps the most popular method of machine translation. They use artificial neural networks to translate text from one language to another. What makes it a preferred method of translation is its high quality and accuracy. This is possible thanks to the artificial intelligence used for the learning of languages. What is more, it is constantly improving its knowledge just like an actual human brain would. This is also where the inspiration for the neural network comes from. Another great advantage of NMT systems is that they are actually able to address many of the limitations that other types of machine learning face.

• Hybrid machine translation

This method is actually an approach to machine translation that is meant to combine the strengths of different machine translation techniques in an attempt to improve the translation quality even more. To make it work, multiple machine translation systems are used together to produce a more accurate translation. It is particularly useful for languages that are difficult to translate, such as those with complex grammatical structures or limited resources. Hybrid machine translation uses the strengths of each system in order to compensate for the weaknesses of the others, which is how the accuracy and fluency of the final product are achieved.

Now that you know more about the different types of machine translations, you can see that they all come with great benefits. This is undoubtedly making modern machine translation an indispensable tool for anyone. With its ongoing improvements, MT has now come to a point where it is faster, more efficient, and capable of translating vast amounts of content. We are yet to see how far it can actually go.

Machine translation has come a long way since its early days, and has shown great promise in breaking down language barriers and facilitating communication across borders. However, we cannot argue that it still has its limitations, particularly in accurately conveying the nuances and cultural references inherent in human language.

To make the most of machine translation, it is important that we carefully consider the context and purpose of the translation, as well as the limitations of the technology. Additionally, post-editing by human translators can greatly improve the accuracy and readability of machine translations. As machine translation continues to develop and improve, it has the potential to revolutionize global communication even more and connect people in ways that were once impossible.