Machine translation vs. computer-assisted translation. Wait! Aren’t they similar? They do sound similar, but in reality, they are poles apart. The translation world can indeed sound complex sometimes. But once you understand the roles of each translation tool, it will be a cakewalk for you and your translation project.
Understanding the difference between machine translation and computer-assisted translation will help you understand and learn more about these tools that professional translators use daily. They are both used in the translation process but have entirely different roles.
Want to learn more about the debate about machine vs. computer-assisted translation? Then read this blog to understand the difference. We will explore and understand the types of machine translation and also what components are used in cat tools.
So, let’s get started.
What is Machine Translation?
Did you know that according to the latest statistics, the machine translation market size is expected to grow by 7 billion by 2032? Now let’s understand the definition of machine translation. Machine translation is generally defined as a technology that is particularly based on a computer algorithm.
It is a subfield of artificial intelligence and computational linguistics that focuses on systems to automatically translate text or speech from the source language to the target language. But machine translations are still considered far from perfect, and machine translation post-editing by humans is often required in machine translation works.
Indeed, machine translation has made significant strides in recent years. However, it still struggles with idiomatic expressions and cultural contexts and requires human translators to proofread the translated work.
Types of Machine Translation
There are various approaches through which machine translation is classified. The three primary categories of machine translation systems are listed below.
1. Rule-Based Machine Translation
Rule-based translation is an approach that uses a set of rules to translate text. All these rules are manually created by linguists and human translators, and they cover the syntax, grammar, and vocabulary of both the source and target languages. Rule-based machine translation relies on grammatical rules and dictionaries to perform the translation process.
2. Statistical Machine Translation
The SMT system approach uses large amounts of bilingual text to learn that phrases and words in the source language correspond to phrases and words in the target language. This approach applies statistical models to predict the most likely translation based on the patterns and frequencies found in the data.
3. Neural Machine Translation
This NMT is the most recent and advanced approach, as it uses artificial neural networks, particularly deep learning models, to understand translated text. These systems are trained on very large datasets of bilingual text and can capture contextual nuances, resulting in quality translations. Popular examples of neural machine translation include Google Neural Machine Translation, Google Translate, and open AI GPT models.
How Does Machine Translation Work?
As mentioned above, there are several approaches and types of machine translation to determine how machine translation works. But all these types of machine translation out there need to follow a basic principle.
Machine translation typically works by relying on learning models and algorithms to translate text from the source language to the target language. Firstly, the source text is filtered and organized, and then the machine translation is trained with various examples for both the source and target languages.
This will allow the machine translation system to understand how phrases are structured. After that, the machine translation engines can produce or translate text and speech based on the insights learned from the prior training.
However, these machine-translated works often need post-editing by a human translator. There is often a need for refinement for this machine-translated work that involves human involvement.
What is Computer-Assisted Translation?
One tool that is utilized in the translation process to help automate it is called computer-assisted translation. It is a translation tool that allows professional translators to handle translation processes more efficiently, faster, and consistently.
The commuter-assisted translation tool is generally used by translation and localization companies and language service providers (LSPs). Also, CAT tools are used by translators who are working on a freelance basis.
CAT tools include several components, like term bases, translation memory, and many more, which we are going to discuss in detail later on. With the development of the computer and networking sectors, so have all of these tools. CAT tools work on software on a computer or within a cloud-based system that can be easily accessed by multiple users simultaneously.
Components of CAT Tools
CAT tools are somewhat similar to text editors, with some additional features that are useful in the translation process. Some of the common components of CAT tools are listed below.
1. Termbases
Termbases are known as translation glossaries that are built from frequently occurring phrases and words like brand names and technical terms. They are generally used to translate phrases and words to assist professionals in maintaining consistency.
2. Translation Memory
Translation memory is a component of a computer-assisted translation tool that records previously created translations. Whenever there is a similar or identical segment found in any translation project, the translation memory uses previously saved translations.
3. Quality Assurance
It relies on various combinations of technology and processes to prevent all the errors that arise in a translation project. Continuous and thorough proofreading in any translation project is required, and quality assurance is a technology that assures the same. Quality assurance begins when the translation project starts and lasts until the final format is finalized.
Machine vs. Computer-Assisted Translation: Major Differences
Some of the major differences between machine-assisted and computer-assisted translation are listed below.
1. Time
Machine translation takes less time as compared to CAT tools. In machine translation, you just need to copy and paste the source text. Just as we do with Google Translate, where we copy and paste the source text and enter the target language that is desired, the output is generated in 1-2 seconds. Whereas in CAT tools, there are significant components like translation memory and termbases that help professional translators complete the translation project. And that requires a significant amount of time to complete the translation project.
2. Accuracy
Machine translation does not account for 100% accuracy, as many languages are complex and dynamic that machine translation does not understand perfectly. Lack of accuracy is considered to be the biggest disadvantage of machine translation. Whereas CAT tools assist professional translators, the accuracy of translation projects relies mainly on the work of professional translators. And as these professional translators are highly trained, they can guarantee the accuracy of translation projects.
3. Cost
Regarding machine translation, many free machine translation programs like Google Translate and iTranslate give you instant translation. But for a huge volume of translation projects, you might need to buy the premium plans of these free machine translation programs to proceed further. Whereas CAT tools are not available for free and you have to pay a good amount of fee to access these translation tools.
It depends solely on the translation project and your translation needs, whether you require a machine translation program or computer-assisted translation. The sole purpose of both of these is to provide translations that are deemed to be the best in all aspects.
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