How Machine Translation Is Making Translators More Productive

Last updated on August 25th, 2023 at 05:14 am

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Translating documents is hard work that requires not just fluency in multiple languages but also in-depth knowledge of translation practices. There has never been a greater need for skilled translation services given the rapid globalization that has been taking place over recent decades. As businesses cross international borders, they need fast, accurate translation services.

Artificial intelligence (AI) and machine learning offer a practical solution to translation services that find themselves swamped with requests. While AI is still a long way from being able to provide professional-quality translations by itself, well-designed machine translation algorithms can boost translators’ productivity by up to 60 percent. As a result, translation companies are better able to keep up with growing demand and provide clients with better, faster service.

What is Machine Translation?

The most sophisticated form of machine translation is known as neural machine translation (NMT). This process can be combined with AI systems to produce valuable tools for human translators. Business owners who want to see the difference for themselves can visit Zab Translation Solutions online. Otherwise, read on to find out how machine translation is improving translators’ speed and efficiency rates.

NMT is unlike the translation solutions of the past in that it was designed to simulate the neurons in a human brain. Like a person, NMT programs can collect data and access it at any time, using a growing collection of information to make connections between different words, phrases, and their contexts.

Faster Turnaround Times

Machine translation is quick because AI and machine learning algorithms don’t need to think or evaluate. They can translate millions of words per second, which helps human translators work at much faster rates. When translators can incorporate machine translation into their daily workflows, the translation service can offer faster turnaround times to clients, which will be especially helpful when working on tight deadlines.

The average human translator can usually translate around 2,000 words per day. Adding machine translation into the equation can speed up turnaround times significantly. Translators can use the algorithms to help with both producing the translations, themselves, and with post-editing work.

More Precise Outputs

The use of machine learning algorithms means that machine translation programs constantly improve their output. The more content translators feed into NMT systems, the greater its advancements will be. Modern machine translators can be trained to predict sequences of words that should appear in translations based on their tone and context, which can improve the accuracy of the outputs.

In many cases, machine translations are so accurate that human translators need only review the work during a post-editing process. Of course, it takes a good deal of time for NMT programs to learn and grow their knowledge bases, so human translators still play an essential role in the process. In most cases, though, they can focus more on localization rather than general translation services, offering clients a higher quality of translation as well as faster turnaround times.

Effective Management of Large Projects

It’s sometimes the case that translation companies receive requests for projects on an impractically large scale. Legal cases offer one excellent example. Lawyers and other professionals need access to full transcripts, plus all of the relevant evidence, and they’re often working on tight time frames.

Cross-border litigation cases have historically placed unreasonable demands on translation teams. These project requests often involve translating millions of words in just a few weeks, plus scanning documents for key phrases and terms. It was almost impossible to produce high-quality work on that scale and time frame before the invention of NMT.

NMT systems can sift through foreign language documents remarkably fast to help human translators find relevant terms. Thanks to machine learning, they can also remember those terms for later use. The process of translating long transcripts becomes much easier when teams have access to NMT technologies.

Reduced Busy Work for Translators and Administrators

Official documents written in any language can be mind-numbingly repetitive. Automating the translation of these repetitive sections of text can take some of the busy work away from translators, saving them time, money, and a lot of headaches.

Machine translators can also handle myriad administrative tasks related to project management. They can assign responsibilities to either AI algorithms or human translators and ensure that everyone stays on task, saving the company both time and money. Automating administrative tasks and repetitive busy work can be especially helpful when working with large projects.

Content Translated Simultaneously Into Multiple Languages

It’s often the case that businesses must have content translated into multiple languages. The content could be cross-border communications, product descriptions, marketing materials, and more. These days, it’s common for companies to plan global rollouts of new products, which requires a massive effort to translate all of the required information across many languages.

Without machine translation, companies tasked with completing these multi-language projects must devote an unreasonable amount of time and resources to managing many separate but related projects. While it’s true that the translation service will still need at least one person who speaks each of the required languages to edit the content, machine translators provide the initial work in seconds instead of days or weeks. Just keep in mind that because NMT systems learn as they are fed new information, translations into languages that are less commonly used may have more errors.

More Time for Complex Localization Tasks

Localization is a complex task that requires not just knowledge of both languages but also of the culture of the people reading the document in the target language. As of now, AI and machine learning algorithms are not up to the task, so it falls to human translators. Saving time on basic translation production means that translators can devote more of their workdays to localization and other more intricate aspects of project management.

Streamlining the Translation Process

The integration of machine translators with translation management systems allows companies to streamline workflows, automate repetitive tasks, and connect the entire translation team. This level of connectivity saves translators and administrators, alike, a lot of time. The extra time saved by streamlining the translation process can then be put into reviewing post-edited texts more thoroughly and providing better customer service.

Improved Scalability

Even translation companies that are assiduous about planning and project management sometimes wind up with unmanageably large workloads. In some cases, a single project can create an unreasonable demand for translators. With NMT technology in place, translation companies can scale up to meet increasing demands without having to broaden the project scope by hiring new translators, which can cause significant delays.

Translation companies integrate machine translation by using the output and then polishing the translation by a professional translator. It significantly reduces the translation cost, and since the machine does most of the work, the translation process is much faster, which can be crucial for businesses. By continuously post-editing the machine translation output, users help the machine learn and enhance its translations for future projects.

Quick Translation of Repetitive Projects

Manuals, user guides, and reference materials are all good examples of repetitive projects that create an unreasonable amount of busy work for translators. Taking advantage of machine translation allows teams to reproduce the content in various languages much more quickly. Each time the company gets a request for a product guide in the same industry, to give just one example, feeding the information into the NMT system and making edits as necessary improves the machine translator’s ability to reproduce repetitive works.

More Time to Focus on Post-Editing

When used properly, machine translations provide a starting point for human translators. The machine translation post-editing process is essential in that it ensures that the final works are not just accurate but also conveyed in the right tone. During the post-editing process, human translation teams review the NMT system’s output and edit it for flow, clarity, and precision and localize the material as needed.

In some cases, only light post-editing is required. Human translators providing only light post-editing just need to make sure there are no critical errors and that the translation is grammatically correct.

Heavy post-editing methods are more in-depth. During this process, translators carefully read through and revise the content to make sure the final piece is accurate, precise, and industry-appropriate.

Enhanced Productivity in Niche Areas

Machine translation can improve productivity across an entire company’s workforce, but there are some areas where it’s more helpful than others. NMT systems are particularly good at enhancing productivity for translators working with:

·         Videos

Internal communications


Frequently updated web content

Other fields that require the translation of large amounts of repetitive text

The boost that machine translation gives to industry-leading translation service providers allows them to offer a greater range of options to clients and focus on challenging tasks that can only be performed by humans.

The Future of Translation

Machine translation represents a huge step forward when it comes to facilitating communication between people who speak different languages and come from diverse cultures. In a rapidly globalizing world, it can make all the difference.

Translation services and independent translators can benefit significantly from integrating NMT programs into their daily workflows already, and the technology will only continue to improve. While it’s doubtful that machine translators will ever be able to replace human workers, NMT systems have a promising future. Translation services that want to keep up with the competition should begin implementing this thoroughly modern solution now.

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