In today’s globalized world, machine translation is widely available and can be very helpful for businesses aiming to expand their global reach. However, if used incorrectly, machine translation could seriously damage your company’s reputation, offend customers, and even lead to legal liabilities.
Most companies looking into global expansion use MT translation software to translate their content from one language into another without human intervention. Although MT software helps to speed up the translation process, the result is not always optimal so you would need to have a post-editor take a look at it.
In this article, we look at the core types of machine translation and outline how to choose the best one for your needs.
Types of Machine Translation
There are four main types of machine translation, and each one examines and treats text uniquely: neural machine translation (NMT), statistical machine translation (SMT), rule-based machine translation (RBMT), and hybrid machine translation (HMT).
Neural Machine Translation
Neural machine translation (NMT) has its base on the neural networks in the human brain. It uses artificial intelligence to continuously learn new languages and improve the languages it already knows. Once trained, NMT becomes significantly faster and more accurate. The first machine translation engine to employ neural language processing—which gains knowledge via use—was Google Translate.
Due to its accuracy and scalability, neural machine translation has quickly become the preferred method of machine translation. This technology has a wide range of possible uses, from automated customer care to real-time language translation in websites and apps.
Rule-Based Machine Translation
This type of machine translation uses a set of grammatical rules to analyze the source language and create content in the target language. Rule-based machine translation (RBMT) systems break the text down into words, translate each one separately, then adjust the morphology and harmonize the syntax. This type of machine translation has a few drawbacks:
Because of its dependency on lexicons, translation becomes efficient after a considerable amount of time.
You need to add languages manually.
The translated material often requires a large amount of post-editing by humans.
Statistical machine translation (SMT) relies on statistical models to generate translations. In other words, the system learns how to translate the content by analyzing collections of existing human translations called bilingual text corpora. The objective of SMT is to determine how certain words and sentences in the target and source texts relate to one another.
It is best to use statistical machine translation only for basic translation because it ignores context, which frequently results in inaccurate translation.
Hybrid Machine Translation
As the name suggests, hybrid machine translation (HMT) blends rule-based machine translation and statistical machine translation to strengthen each system’s positive aspects while minimizing its negative ones. HMT uses translation memory, which significantly enhances the quality of translation.
Although hybrid machine translation blends the benefits of both rule-based and statistical machine translation, it still has certain disadvantages, such as the need for thorough proofreading by human translators.
What Type of Machine Translation To Use?
To decide which type of machine translation best suits your needs, you must take several factors into account:
- Your language pairs. Which type of machine translation you choose will also depend on the language pairs you’re working with. For example, if you are translating Latin-based languages with comparable grammatical structures and syntax, statistical machine translation (SMT) can be a suitable option.
- Your industry. Does your content use complex technical terminology? In that case, of the above-listed four types of machine translation, neural machine translation (NMT) is the best option because of its accuracy.
- Your budget. Although employing machine translation software might seem connected with considerable investment, the cost is minor compared to hiring human translators for every language you may need in your translation projects.
Choosing the Best Type of Machine Translation
Each type of machine translation has its benefits and downsides. Which one you decide to use will ultimately depend on your unique requirements and financial constraints. Think about whether you need quick translations on a tight budget or anticipate working on more complicated projects that demand greater accuracy.
At the end of the day, quality translation and localization can make your business available to a large number of new clients who speak different languages, so investing in a quality machine translation system will pay off in the long run.
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