What Types of Machine Translation Should You Use?
It has long been a goal of computer science to use computers to automatically translate text from one language to another. The continuous achievements in natural language processing, artificial intelligence, and computing power help us reach closer and closer to this goal. Thus, machine translation has become a viable tool in widespread use for the last decade.
In today’s post, let’s talk about the concept and different types of machine translation as well as finding out which type is your right choice.
What is Machine Translation (MT)?
Machine translation employs artificial intelligence (AI) to automatically translate content between languages without the involvement of human linguists. Google Translate, Bing Translate, Microsoft Translator and Amazon Translate are a few popular and familiar names of machine translation tools.
Many people are likely to get confused between machine translation and automated translation and use them interchangeably. They, in fact, serve entirely different purposes. Automated translation refers to the automation built into computer-assisted translation tools (CAT Tools) or translation management systems (TMS) that automatically translate repetitive segments.
Learn more about the differences between MT and CAT Tools
Although at a certain stage in the translation process, automated translation can assist the machine translation of text, they cannot be mistaken as one.
What are the Benefits of Machine Translation?
Even though machine translation has always been at the centre of reliability and quality debates, the great benefits it brings cannot be denied.
One of the most important advantages of machine translation is speed. Any machine translation can translate a large amount of text quickly. While its accuracy cannot match human translators’, it is obvious that machine translation wins when it comes to speed.
At first, purchasing machine translation software may appear to be expensive. However, compared to hiring human translators for many translation projects in the long run, this cost is almost nothing. You will have access to the translation software whenever it is needed after paying for it once. And if you don’t want to pay, there are still many free solutions available.
In addition, machine translation has the ability to memorize and learn words, then reuse them wherever appropriate.
Types of Machine Translation
Below are the four most common types of machine translation:
#1. Statistical Machine Translation (SMT)
Statistical MT generates translations based on statistical models whose parameters are derived from bilingual text analysis. Its goal is to identify the relationships between words, phrases, and sentences in the source and target texts.
As statistical MT does not take context into consideration, leading to frequently incorrect translations, it should only be used for basic translation (to understand the gist of a text).
#2. Rule-Based Machine Translation (RBMT)
Rule-based MT relies on grammatical rules to translate. To generate the translated sentence, it performs a grammatical analysis of the source and target languages.
Rule-based MT has several serious drawbacks. First, its reliance on lexicons means that efficiency is attained only after a long period of time. Second, languages must be added manually. Third, it necessitates significant amounts of human post-editing due to its poor quality.
Therefore, it has some applications in very basic situations where a quick comprehension of meaning is required.
#3. Hybrid Machine Translation (HMT)
Hybrid MT HMT, as the name implies, is a combination of Statistical MT and Rule-based MT. It makes use of translation memory, thus, the quality is improved much significantly.
Despite blending the advantages of both Statistical MT and Rule-based MT, hybrid MT still has some drawbacks. One of the most significant is the need for extensive proofreading from human translators.
#4. Neural Machine Translation (NMT)
The neural MT model, based on the neural networks in the human brain, employs artificial intelligence to learn languages and constantly improve that knowledge. Once trained, it becomes more accurate, and much faster. It is also easier to add new languages. Google Translate was the first machine translation engine (MTE) to use neural language processing, which learns from repeated use.
Some popular neural-based machine translation engine
The single system used in Neural MT can be trained to decipher texts in both the source and target languages. As a result, specialized systems like those found in other machine translation systems (particularly SMT) are not needed.
For these reasons, neural MT is quickly becoming the industry standard in MT engine development.
Which Type of Machine Translation Should You Use?
In general, Statistical MT is a popular method as it does not require a regular update of language rules like Rule-based MT. Meanwhile, Neural MT is unquestionably the most advanced option. To decide which MT type is suitable for your projects, you need to take many factors into consideration:
- Your Budget – Compared to other types of MT, neural MT is the most expensive engine to train. However, the quality is worth the cost differences.
- Language Pairs – Statistical MT is a sufficient choice if you need to translate Latin-based language pairs which have similar grammatical rules and syntax.
- Industries – If your content contains complex technical language, neural MT will be the best choice among the 4 common types of MT.
- Use Purposes – With the aim of achieving basic employee communication or internal documentation, basic MT can be used to save you costs. Otherwise, for external purposes such as sales and marketing materials, the involvement of human translators at a certain stage is necessary. You can use MT for translation and human translators for post-editing (MTPE).
Have you found a suitable MT engine to use for your upcoming projects? If you are still unsure, talk to one of GTE Localize’s localization experts. GTE Localize is a professional language agency. We offer a wide range of translation and localization services, from machine translation post-editing (MTPE) to 100% human translation.