What is Automatic Translation? Is it Right for Your Localization Projects?
Robots replacing humans is a hot topic these days, and translation was one of the forerunners in this machine versus human contest. The aim of any automation is to save time by removing the need for humans to undertake repetitive jobs in the workplace, freeing them up to focus on more important tasks. For example, with a little human help, machines can build cars on conveyor belts but have their limitations when it comes to designing and marketing them. The same is true of translation – automation definitely has its time and place.
How does automatic translation work?
Automatic translation is an entire process that takes the content you’ve created and manages the translating, publishing, and quality control of it. Machine translation is a tool within this process, speeding up the initial translation of your content. With a successful automatic translation system in place, your content flows from start to finish, your workforce is more streamlined, and the process is more cost-effective. However, human intervention needs to remain a vital component of the process depending on the goals of the content. At BLEND, we offer automatic translation tools that accurately translate and localize your products, services, and websites translation. You can configure the process as you see fit, choosing as much or as little automation as you want.
Types of machine translation
Translation was one of the first aims of computer power in the 1950s, but computers had to be “taught” how to translate anew with each language. The complexity of this and the enormous amount of data generated remained beyond usable computer capability until Google Translate was launched in 2006. This led to today’s software that can cope with translating huge volumes of text almost immediately. Natural Processing of Language (NLP) takes one natural language and translates it into another natural language. There are now four main types of machine translation tools in use, all working on NLP:
- Statistical Machine Translation (SMT): With SMT, huge volumes of bilingual content are studied to create statistical models. Direct correspondence is found between a word in the source language and a word in the target language. Google Translate is probably the best-known version of SMT. However, it’s unable to take into account the context of the source text which can lead to poor-quality translation.
- Rule-Based Machine Translation (RBMT): This works by examining the grammar of both the source and target languages, and then using basic rules to complete the translation. The result can require extensive editing.
- Hybrid Machine Translation (HMT): This is a blend of the first two systems which operates more successfully. As it works, it creates and builds up a translation memory leading to better quality work the more it is used. It does still require a considerable amount of human editing.
- Neural Machine Translation (NMT): Much more complex and expensive to develop and use, NMT creates neural network models based on the human brain. From this, statistical translation models are built, which can unravel the complexities of both languages.
The place of machine translation within the automatic translation process
Modern machine translation is well suited to very structured and technical content such as legal, financial, and IT work. It is also useful for internal communications where 100% accuracy can be overlooked in favor of speed. Its limitations become apparent when content is more creative and colloquial such as in branding, marketing, and any content that customers encounter. Machine translation provides a useful and speedy starting point, but the results must be checked and edited by qualified human translators. These post-editors must not only check language accuracy and quality, but also that the content is properly localized – something still out of the reach of machine translation.
The benefits of using machine translation
- It’s faster and cheaper than human translators
- It’s good for translating large amounts of content when general meaning is enough
- It works for internal communications when 100% accuracy is not essential
- It’s useful for translating text that a human translator will improve (the transcreation process)
- It can be “trained” for specific fields such as legal documentation
- The range of languages available is potentially unlimited
The limitations of machine translation
- The results can vary from inaccurate to potentially dangerous
- Translations lack context
- It can’t cope with hidden meanings, colloquialisms, metaphors, style, tone, etc.
- It can’t be used where lack of accuracy could endanger life such as, for example, aviation manuals, or medical equipment instructions
BLEND offers a structured combination of both machine and automatic translation online. We have a team of experienced and knowledgeable translators who work with the highest accuracy. They begin with machine translations, and then review the results for accuracy, capture the context, add creativity, and ensure the final result is successfully localized to help your business evolve and grow. Contact us to discuss the right solution for your multilingual strategy.