Welcome to Fast Trans Translation



Machine translation: what is it and its types?

Machine translation

Translation is a crucial tool for understanding the cultures of different peoples as well as for enabling easy communication between nations with different languages and customs. Some people mistakenly think that translation is a comprehensive translation without any types included; in reality, translation includes a variety of types, including machine and human translation. But what exactly is machine translation? and how can one use it?  We are going to explain this to you today.


Definition of machine translation

Machine translation is one of the types of translation that is done by using machines and software, and the translator here is a computer device and automated programs, not a human translator. All you have to do is enter the text you want to translate from one language to another on these programs, and after a few minutes, the translation process of the text takes place automatically.


Machine translation works by using advanced algorithms; so that the machine or program can translate according to them, and this is according to a set of steps as follows:

  • The text that is translated by this machine is first organized and filtered using a series of steps.
  • After that, the machine’s system is trained and programmed for translation operations by using examples of texts in various languages and translating them in other languages.
  • After that, the machine picks up the abilities needed to examine the samples to comprehend them and identify any patterns or potential issues related to the translation of words or sentences.
  • When new text is entered for translation, the machine then starts utilizing this technique.
  • It is important to note that after receiving the translation, the results may not be precise and often need to be corrected because we occasionally find problems.



What is the difference between machine translation and human translation?

These days, machine translation is used in many professions and businesses. This is mostly due to the diversity and advancement of these translation programs, but human translation is still necessary, and many institutions and businesses still rely on it.

The main and most noticeable distinction between machine translation and human translation is that machine translation is done by machines and programs that have been trained to do so; accordingly, the quality of the translation produced by these methods will be inaccurate, and full of errors. Regarding human translation, as it is done by a human, there is a lower chance of errors in the translated text and a higher level of translation quality.

It is important to note that human translation has to step through machine translation to enhance the translated text’s quality and include emotions that the reader will experience.


What are the types of machine translation?

There are several types of machine translation that are classified according to their mechanism of action, the most prominent of these types are the following:


1-machine translation based on rules (RBMT)

This translation works based on linguistic rules during the translation of texts; it analyzes the text that will be translated according to the rules of its original language and then converts it to the target language after analyzing its linguistic rules. So this type of translation faces a large set of problems due to its dependence on language dictionaries, as it needs to add languages manually, as well as human intervention to review and ensure the accuracy of using the rules after translation into the target language.


2-statistical machine translation (SMT)

Since statistical models are used to link words, phrases, and sentences in the source and target languages, this type of translation relies on guesswork rather than data processing to achieve the most accurate translation. As a result, the percentage of errors made in this type of translation increases. It is best suited for translating basic and obvious concepts only and should not be used for translating lengthy, accurate texts.


3-mixed machine translation (HMT)

This translation is a combination of statistical translation and translation based on rules, which means it is of high quality. It processes data and relies on rules and guesses with each other in the translation process from the source language to the target language. Despite the results of this high-quality translation, it still needs professional human translators to review it after obtaining the results.


4- neural machine translation (NMT)

In this type of translation, artificial intelligence is relied on; it is trained to learn and improve languages continuously, so when a text is presented to it, it handles it intelligently and is translated with high accuracy.


5- Transfer-based machine translation:

This method involves translating from the source language into a transitional text and back again into the target language. This is a lengthy process that involves many small steps.


6- example-based machine translation (EBMT):

A database of bilingual sentences is used by example-based machine translation, which locates examples that are comparable to the input sentence. A translation is produced by the server by combining and modifying these instances. When handling common phrases, this method works very well.



What technologies are used in machine translation?

Through the use of computational tools, machine translation approaches enable the machine translation of speech or text between languages. The following are a few popular methods for machine translation:


1- rule-based machine translation:

This method of translating the material is based on dictionaries and grammar. It consists of an established collection of guidelines that control the translation procedure. However, this method has limitations since, while it may work well for some language pairs, it might not be appropriate for languages with different grammatical and linguistic structures.


2- Enhanced learning in machine translation:

Machine translation models have been improved through the use of enhanced learning techniques. The system can produce translations of higher quality because it can gather input on how well translations are done and continuously modify its tests to get better over time.



What are the advantages of machine translation?

Machine translation plays a crucial role in the translation process in modern times, and can be used independently, or in conjunction with human translation. Machine translation has three advantages that you get when using it in your translation operations:


1-high flexibility:

The majority of automated machine translation resources support at least 50–100 different languages. With the least amount of time and work possible, you may localize your content to numerous audiences by using these advanced tools that translate many languages at once.


2-speed translation processes:

Machine translation can translate millions of words for large-scale translation projects in a very short time. Even though the speed of translation operations is one of the main advantages offered by machine translation, what is no less amazing is the high capacity of artificial intelligence, which is the fuel of machine translation. It improves the quality of its translation operations for you by increasing the content that you ask it to translate.


3- lower translation costs:

Even when human translators are needed to edit texts that have been translated by machine translation, machine translation servers are effective in reducing translation costs and the time it takes. Machine translation technologies take the burden off human translators by providing them with various translation drafts for them to edit.


4- the ability of machine translation to be specialized:

Machine translation can be trained on specific areas using data specific to the target area and its specialized terminology. This is done by collecting and using large volumes of translated texts from the target field, such as medical, legal, or technical documents. Machine translation systems can learn to understand the specific terms used in the field and translate them accurately.


5- consistency in the use of terminology:

Consistency in the use of terminology refers to the use of consistent terms in different translations, which is important for maintaining accuracy, clarity, and readability. For For example, if a term is translated differently every time it appears in a document, this can lead to confusion for the reader, and his inability to properly understand the text.



Disadvantages of machine translation

Despite the many advantages and benefits of machine translation, there are multiple disadvantages, and the following are the most prominent of these disadvantages:


Low translation quality

Machine translation fails to provide translated text with high accuracy, and we note the low quality of the text you are translating, due to the presence of some fixed terms and expressions that you do not deal with properly during translation, and it does not rely on accurate sources in the translation process.

Machine translation does not provide you with an accurate translation as human translators do; a human translator understands the text well before translation so that he can translate it accurately while preserving its meaning and its concept, unlike machine translation, in which the meaning of the text is not understood, but it is translated literally for words and sentences from one language to another only.


it contains mistakes

We note that there are many grammatical errors in machine translation, and of course, these errors affect the content and the reader, and they may also affect the meaning of the translated text.


What is the importance of machine translation?

The importance and benefits of machine translation appear in many different points, among which:

  • The translation process is instant and fast.
  • A large number of words can be translated in seconds or minutes immediately after entering the text directly.
  • Supports a large number of different languages.
  • low cost.


Some of the machine translation tools

There are multiple applications and different tools that are used in machine translation, and the most famous of these applications are the following:


1- Google Translate

The Google Translate application is one of the most widely used machine translation programs around the world; it supports a large number of languages, reaching more than 100 languages, and a large number of individuals and companies from different countries of the world rely on it for translation.


2- Naver Papago

The Naver Papago application is one of the best translation applications based on neural translation, as it learns from its mistakes in translation and works to understand the type of translation that the user needs to provide. 


3- DeepL Translator

The DeepL Translator website is one of the machine translation applications that rely on artificial intelligence, and thousands of new users use it monthly to provide translation in multiple languages.


4- Yandex Translate

Yandex is an application that stands out for its speedy translation and support for a wide range of languages. It is built on statistical machine translation, which goes through development and improvement to become self-learning and deliver high-quality translations to users.



What is the history of machine translation?

The idea of machine translation is not new, despite what some people may believe. Its origins can be traced back to the 1930s, and over the years, it evolved and took shape into the machine translation technologies that are now a necessity in our society.


1-the Thirties of the Twentieth Century:

In the Thirties of the twentieth century, specifically in 1933, the Soviet scientist Peter Troyansky presented a machine that selects the right words to translate a text and then prints it to the Academy of Sciences of the Soviet Union. That machine was then very simple and primitive technologically.


2-sixties of the twentieth century:

The American Albak Committee considered machine translation to be expensive, imprecise, and not promising in 1966, at which point fruitless attempts to enhance the technology continued into the sixth decade. The committee advised researchers to concentrate exclusively on creating a traditional dictionary.


3 – the seventies of the twentieth century:

The 1970s witnessed the emergence of the first concepts about structured machine translation. In an attempt to mimic the actions that a human translator takes when working with text, scientists and researchers attempted to replicate the labor of human translators.


4 – the nineties of the twentieth century:

In early 1990, at the IBM Research Center, an automated translation system was demonstrated for the first time that knew nothing about grammar or linguistics as a whole. The automated system relied on its ability to analyze similar texts in two different languages and try to understand the patterns and similarities between them.


5- The Beginning of the Twenty-First Century:

At the turn of the Twenty-First century, some software development companies established machine translation services over the Internet. In 2008, Japan developed text message translation services on mobile phones, followed by China in 2009, where it included machine translation services in the mobile phones it produces.


6-the current time:

Recent years have witnessed significant advances in machine translation technology, with Google’s research on machine translation pointing to an optimistic future for this field of translation.


After learning about machine translation and its different varieties, some people may conclude that the development and implementation of these tools will put human translators at risk. However, this notion is false because, despite their best efforts, machine translation programs will always make mistakes and cannot provide texts with the same level of accuracy and quality as human translators. Additionally, texts that have been machine-translated still require human review to ensure accuracy.

Related Content