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Machine Translation API

How do you know when to use machine translation for your job or business? Some translation jobs are better left to human translators, but a growing number of employment are significant for machine translation(MT) or a mix of machine and human translation. As AI improves, modern machine translation API has several benefits that are all its own. Here are five good reasons to use machine translation to give you a sense of the situation.

Machine Translation Is Faster

One of the best things about machine translation API is its quick work. MT can translate quickly enough for real-time business communication when set up correctly. An MT array can translate hundreds of thousands of words per second with the right server setup, which is often provided in the cloud. When used with one round of human post-editing, MT can cut turnaround times by 35 percent or more, depending on the project’s size.

Also Read: Five Reasons Why You Need App Localization?

Improve Terminology Consistency

Another benefit of machine translation API is that it ensures that terms are always used in the same way. This is especially important for projects that are more significant because it makes it easier to track the words being used. Large human projects would need to be translated by more than one person simultaneously. This makes it harder to keep the same tone and control the terminology than machine translation.

Also Read: AI-led English to Marathi translation solutions can increase the engagement of the audience

 Drive down The Total Cost of Translation

Human translation is 100 times more expensive than machine translation. This is true even if the deployment is customized and secure. Even when the technology is used with human post-editing, it still cuts costs by 15–30%. The key is to train the MT engine to almost perfectly copy your voice, tone, and style.

Also Read: Is Website Localization Important For Edtech Companies In India?

Great for Sifting Through Large Amounts of Data

Machine translation is also helpful when you need to translate a lot of content quickly, like chats in real-time or large-scale legal cases. A job that would be impossible for a person to do. In these situations, machine translation API makes it easy to quickly sort through documents written in a foreign language, look for relevant words, and remember them for later use.

Also Read: Why Is The Banking Sector Availing English To Hindi Translation Solutions?

It Makes It Possible To Balance Cost, Quality, And Time

When MT is used as part of a complete enterprise solution, it makes it possible to change cost, quality, and time in ways that have never been possible with language solutions. The machine translation API also helps medical clinical trial organizations that need translations that are as good as those done by humans but want the best price and fastest turnaround. Before AI-powered machine translation was added to the language solutions workflow, it was impossible to give customers a lot of freedom.

 Provides A Starting Point For Translation For Human Production

The machine translation API is now commonly used in almost half of all translation work. If an MT engine is trained well enough, it can give a professional specializing in a specific industry a better place to start. This is sometimes called post-editing, a single pass over the MT output. Even with good training, MT post-editing will still lower the overall quality of the translation, but it is much faster and cheaper.

Also Read: The Importance of English To Malayalam Translation in Publishing Media

Machine Translation Is More Efficient

Using machine translation API has many benefits, and speed is one of them. When designed well, MT can provide the speed of translation needed for real-time communication in the workplace. With the proper server infrastructure, an MT program can translate hundreds of thousands of words per second typically hosted in the cloud. When MT is used with one round of human post-editing, the turnaround time can be cut by up to 35%, depending on the size of the project.

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