In today’s world of rapidly-advancing technology, contrivances can get a little hard to follow- jargon-filled nuances, imagery that looks alien to the untrained eye, and developments that both amaze and bewilder the mind. Day by day, technology gets a little bit more complicated, confusing, and outright convoluted. Let’s be honest for a moment, we all find technology difficult to understand.
Companies, once household names in individual nations have transcended onto a global level with the aid of technology. With globalization come many benefits but also myriads of difficulties--localization being a major one.
Have you ever been online looking for something and come across a website in a language you don’t understand? It feels a lot like traveling in a foreign country. You can’t comprehend the language, the signs are foreign, you can’t compute the currency, and as you look frantically around for some form of familiarity, nothing jumps out.
If you understand this feeling, then you already understand the necessity of localization. Localization is the process of adapting a product or content to fit the linguistic and cultural norms of another specific market. If localization is successfully achieved, a product or service will have more relevance within the local culture. Here we are going to give a simple, easy-to-understand introduction to the technology that has allowed us to communicate globally.
The Technical Bits
The technology sector has developed various methods to address the difficulties of localization, and to make the products and services that it offers superior to now outdated systems. The most crucial of which are Language Technology and Machine Translation: technologies that attempt to translate human languages in a contextually correct manner.
As defined by the German Research Center for Artificial Intelligence, language technology, sometimes referred to as human language technology- comprises computational methods, computer programs, and electronic devices that have been designed to specifically analyze, modify, and produce texts. To work as they do, these systems are created with a base knowledge of human language and are therefore defined as the engineering branch of computer linguistics. With the assistance of natural language processing, language technologies help a computer--or any other electronic device--to understand the differences between human and computer language.
Historically, computers have only been able to comprehend structured and standardized data- when programmers produce applications, software, webpages, or do any coding, they give the computer a set of rules telling it how to operate. In contrast, people have been writing and adapting as well as evolving languages for centuries. In many ways, from our first day of existence, our brains are fine-tuned to understand the tremendously complex web of contributing factors to our words, phrases, and the semantics that surround them.
This ingrained understanding allows us to empathize with what we read. We feel the emotions that topics evoke and we naturally understand the use of certain words. Essentially, this is because we can see the context and cultural effects behind the writing--which a computer cannot.
Machine Translation Methods
Machine translation (MT) is a technology that automatically translates text using termbases and advanced grammatical, syntactic and semantic analysis techniques. In its earlier days of conception MT came in two forms: ruled-based machine translation (RBMT) and statistical machine translation (SMT).
The RBMT method generates translations based on morphological, syntactic, and semantic analysis of the input and target language: German to English, let's say. The system generates constant, resolute translations without having to rely on a bilingual corpus--a collection of original texts in one language, and their counterparts in another. Here is an example of a translation:
German: Starten Sie die Wiedergabe am angeschlossenen Gerät und stellen Sie eine moderate Lautstärke ein.
English: Start the rendition at the attached equipment and adjust you a moderate volume.
Statistical machine translation, as an alternative method, generates translations from large bilingual text corpora, based on statistical models. This system can almost come across as fluent in every language. Here is an example of the same translation made with SMT:
English: Playback starts from the connected device and set a moderate volume.
Refining the Point
As you can see, neither RBMT or SMT gives a perfect translation. To rectify this issue, tech giants are implementing natural language processing within machine translation, which utilizes entity analysis. This system analyses the entered text and identifies all of the words that have real-world semantic meaning--or, significance to a human--allowing the computer to look deeper into the meaning of certain words or phrases, and indeed, the potentially differing translations when localizing text.
With this in mind, building upon the foundations of both RBMT and SMT, AI waded into the translation-sphere. With it came neural machine translation (NMT), which uses the foundations of AI and machine learning and advances from there. Look what this newest machine learning technology can do:
German: Starten Sie die Wiedergabe am angeschlossenen Gerät und stellen Sie eine moderate Lautstärke ein.
English: Start playback on the connected device and set a moderate volume.
Voila! A well-structured, correctly worded sentence translated from German into English. The advancement of our understanding behind machine technology and the implementation of newfound solutions has led to computer translations becoming an efficient way to implement localization.
While there are still problems surrounding globalization, including policies, taxes, and regulations, the technology sector has, at least, developed language technology and machine translation to the extent that languages originating from the same family-tree can be translated easily.
Drastic steps have been made in the world of AI in an attempt to turn computers from binary to rational-thinking machines. While there is still a long way to go, we can at least say that the progress thus far is enabling localization and translation to continue its growth. And with the emergence of globalization, the need and demand for translation and localization solutions are growing.
Until that time when a computer can actually think like a human, there’s Andovar. We are a global provider of multilingual content solutions. We provide translation and turnkey localization services for websites and software, ensuring your content flows with elegant prose. Our headquarters are in Singapore, with offices across Asia, the U.S.A., and the U.K. All of our work is done in-house with the help of native-speaking talent, using state-of-the-art machine translation and external linguistic resources. Andovar is your one-stop destination for translation and localization services at a competitive price.
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