Translation of languages is a well-known activity that has been present for a long time now, dating back as far as the evolution of languages themselves. Throughout history, there have been exchanges of communications between countries, regions and individuals, aided by one tool—language.
As the world embraces new technology and innovations in the field of science, technology and business, the need to communicate ideas across the borders has been taking a stronghold. This communication, aided by translation, has also undergone some major changes and shifts whereby new technology has replaced older ones and the processes of translation has become faster, more accurate, and better aligned to suit the needs of the exchanging parties.
Here, we take a look at the innovations that have been around for some time in the translation industry and which contribute to the exchange of information across borders and languages:
- Translation Memory
Translation memory, or TM, is a database which stores translations that have been performed by translators in the past. It is a “store” of all the terms and languages that the translators have executed as part of the translation services. Translations are broken down in “segments” which are the language units comprising of phrases, paragraphs, sentences, or headings. Keeping in perspective this increasing database of words and phrases, the translation system suggests translations for recognizable segments in the new documents. In some of the systems, this translation memory lets you choose your industry for your document from a wide set of available options such as sports, science, law, or medicine, enabling to make translation process even easier to execute. These functionalities, coupled with the translation memory upgradation provides the accuracy and consistency required for an expert translation process.
- Machine Translation
A few decades back, when translation services and companies relied on delivering expert translation services, the task of translating large documents and files was handed to human translators. As complexity of the projects increased, however, this human translation was replaced with machine translation.
Machine translation (MT) works exceptionally well in translation projects where little cultural context is required. This means that machine translation is mostly done for the projects that are “technical” in nature. Machine translation is more “consumer-focused”, such as Google Translate which has the capability of translating a string of words quickly. Also known as “automated translation”, MT has three basic types:
- Rule-based system: This type of machine translation uses combination of grammar rules and dictionaries to translate common words. To focus on certain industries and disciplines, special dictionaries are created containing all the common words and phrases.
- Statistical systems: this type “learns” to translate by observing and analyzing large amounts of data for each given language pair. Statistical systems deliver quicker but less consistent translations and can be “trained” to deliver translations for specific industries using additional data related to the sector needed.
- Neural Machine Translation: this is a relatively new approach that uses multiple processing devices to make machines learn through a large neural network. After its successful implementation, neural machine translation has begun to show better translation performance in many of the language pairs in comparison to the statistical system.
The benefits of machine translation are numerous—and reduced cost and increased efficiency are a few of these. The users of machine translation report that machine translation delivers real-time translations, with almost 40% suppliers viewing machine translation as an asset for service differentiation.
- Artificial Intelligence in Translation
The machine translation examples given above are part of the Artificial Intelligence technology shaping the translation industry of the future. The neural machine translation (NMT) is an advanced type of machine translation that is increasingly being hailed as the “future of translation” and has shifted the face of the translation industry towards faster, and more accurate translations. Some of the world’s most well-renowned translation companies such as Microsoft, Google and Amazon, have all invested in delivering AI translations to their customers across the globe and have incorporated neural machine translation as part of this AI drive into their translation processes.
The Last Word:
Translation is a necessity in the world of today where communications have become more advanced and vital. Seeing the various benefits that machine translation offers to the customers across the world, one would be tempted to think that machine translation is the new face of translation and will completely replace human translation, but that is not the case. There are still some unresolved flaws in the machine translation—the inability of delivering accurate translation among the top ones. Machine translation may have eased the translation processes for companies but it can only translate on a sentence-by-sentence basis, meaning that any documents it translates are basically a sequence of translated sentences, rather than a connected and coherent one. Nevertheless, AI translation is the new translation technology being sought out by translation companies and providers across the globe for a more accurate, better, advanced, and professional translation—something virtually unimaginable in the past.