Technological advancement has had a huge impact on business development in all of the world. With globalization as more companies launch their products across the globe, the need for high-quality translation services continues to grow. With that said translations take time and require resources. That is why using computers to translate text from one language to another has long been a computer scientist’s dream. Interestingly it is only in the past ten years that machine translation has become accessible and so widespread in public use. It is due to the evolving and expanding demand for translations. With the global machine translation market size today estimated to reach 3 billion USD by 2027, it is a good time to explore what are the machine translation essentials. In this blog post, we will take a quick glance at the topic of machine translation, its types, and its main benefits.
What is Machine Translation?
To understand why Machine Translation is so popular it is important to know what it is. Basically, Machine Translation or MT for short is the process of using computers to translate one language known as the source into another one known as the target language without the involvement of people. The translation is done through complex algorithms, neural networks, or a mix of both. Today’s most well-known Machine Translation provider is Google translate, although there are several other services that are gaining popularity.
4 Main Types of Machine Translation
As we can see Machine translation is rooted in systems. Machine Translation systems used to work on a set of rules, analogies, or statistics, and the results weren’t always natural-sounding. On the other hand, newer Machine Translation systems try to mimic how the human brain recognizes and makes associations between language pairings. Let’s have a look at the 4 main types of machine translation and how they function.
1. Rule-based Machine Translation (RBMT)
The “traditional approach” to Machine Translation is Rule-based Machine Translation or RBMT. The core linguistic aspects of the source and target languages are covered by dictionaries and grammar rules used by RBMT systems. The fundamental issue with this technique is that, while any error in translation output may be addressed by adding a new rule, implementing these rule interactions on a wider scale can be tedious and costly. There is also a scarcity of good dictionaries from which to gather information.
2. Statistical Machine Translation (SMT)
Statistical Machine Translation or SMT analyzes bilingual corpora and generates statistical rules from them to provide a translation. Statistical Machine Translation can produce more fluent translations for a cheaper development cost. Statistical machine translation is divided into three categories: word-based, phrase-based, and sentence-based. The main distinction is what the system considers to be the fundamental unit of translation. This approach, which was once seen as “the future or translation,” has been largely replaced by modern technology. Google Translate is the most well-known SMT. The fundamental problem with SMT systems is that they have trouble understanding and translating cases, gender, ambiguity, and quirky expressions.
3. Hybrid Machine Translation (HMT)
Hybrid machine translation is a type of machine translation in which different machine translation methodologies are combined into a single machine translation system. The failure of any technique to achieve a reasonable degree of accuracy is the motivation for developing hybrid machine translation systems. Many hybrid machine translation systems have been successful in improving translation accuracy. In fact, there are several popular hybrid machine translation systems on the market available.
4. Neural Machine Translation (NMT)
Neural Machine Translation, or NMT, is a technique that uses artificial neural networks to mimic our brain’s behaviour in linking and encoding information to learn mathematical functions for translation. A neural Machine Translation system, unlike statistical Machine Translation, does not contain small sub-components that must be calibrated separately. Instead, it creates a massive network of interconnected components that the system constantly fine-tunes as it is used. Today’s Machine Translation algorithms are powered by neural networks and deep learning.
Top 5 Machine Translation Benefits
Here are the 5 machine translation benefits that you will encounter if you go for machine translation.
1. Cutting Costs
One of the main Machine translation benefits is pretty much cost-effectiveness. Although professional translations provide more natural-sounding and grammatically correct translation, the cost of human translation is many times more expensive than machine translation. With that said, machine translation helps to cut costs.
2. Saving Time
Another machine translation benefit is how fast it is. When it comes to machine translation machines translate any kind of content almost in no time. This is the one area where we humans are naturally unable to compete with machines.
3. Ensuring Security
Machine translation ensures security. When doing translation through machines you can return a translation in a matter of seconds no matter how short or long the translation is or what type of translation it is. This benefit is particularly valuable for global corporations that translate a large amount of content for internal and external use.
One of the advantages of Machine Translation is that it is ever-evolving as it is programmed for self-learning. Newer Machine Translation systems strive to imitate how the human brain identifies and develops correlations between language pairings along with using a set of rules, analogies, or statistics. This makes machine translation systems a recognizable competitor for professional translators of the future.
5. Translating into multiple languages
It is a known fact that as of now professional translators provide higher-quality translations than machines are capable of. But when it comes to the quantity of languages translators can do translation in, there is only as much as they can do. So for companies who want to get translations in more languages and cut costs, machine translation is the way to go. So translation into multiple languages is another advantage of Machine Translation.
As we can see, machine translation is a great and cost-effective solution to a new demand for translations. But we know that machine translation is not for everyone. In our next blog post, we will talk about which companies can benefit from machine translation and understand which is better: Machine translation, human translation, or hybrid?
Machine Translation VS Human Translation: Which is Best?
[…] Machine Translation is the process of using computers to translate one language known as the source into another one known as the target language without the involvement of people. Being rooted in the systems, the translation is done through complex algorithms, neural networks, or a mix of both. Today’s most well-known Machine Translation provider is Google translate, although there are several other services that are gaining popularity. Machine Translations are fast, scalable, and cost-effective. If you want to learn more about Machine Translation essentials, types and benefits, check it out here. […]
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