What is Machine Translation?

12 mins read

Machine Translation

Machine translation has always been a controversial topic in the multilingual world, but MT is here to stay, so let’s see what are the types, use cases, and how it can help. We’ll also cover which MT engines are available in Crowdin and how to leverage them.

Why do People Use Machine Translation?

People mainly use machine translation to generate translations reducing the translation time and costs. For example, Google Translate, one of the most popular machine translation systems, processes over 100 billion words daily.

Benefits of Machine Translation

Spoiler alert: not every project needs to use Machine Translation, but it’s better to know when it’s helpful and keep this info in mind rather than losing the opportunity to optimize your localization processes. So, let’s see why people choose to use MT in their translation projects.


Machine translation can simultaneously handle a high volume of translations in many languages. So if you don’t have the time or budget to localize your 404 page into 35 languages, you can do that with MT in minutes.

Terminology Consistency

Machine translation can maintain consistency across terminology used in translations. This will ensure a cohesive brand voice and message across different languages, resulting in a more professional and unified user experience.

Please remember, that if you want machine translation to provide consistent translations, you must upload your glossary and train the MT engine.


Machine translation can significantly reduce costs, especially for large-scale projects, as you will not need to hire human translators for simple and minor tasks. Please remember, that while you’ll be saving time, you might lose on quality, so you have to understand which one is the priority for this specific type of content. We recommend, using MT for content that is not mission-critical.

Efficiency and Speed

Machine translation provides quick translations, saving time and effort compared to manual translation. It allows for near-instantaneous translation of large volumes of content, making it an efficient solution for organizations and individuals with time-sensitive translation needs.

Importance of Machine Translation Post-editing

Machine translation may not always produce perfect translations and can lack the nuances, cultural understanding, and accuracy that human translators provide. Human review or professional translation may be necessary to ensure the highest quality and precision. This is where the post-editing of machine translations comes into play.

Post-editing of machine translations is reviewing and modifying machine-generated translations to ensure accuracy, fluency, and adherence to the desired quality standards. It involves human intervention to improve the output data produced by machine translation systems.

Use Machine Translation with Crowdin

What are the Most Stages for Machine Translation?

Neural Machine Translation

NMT models are trained on large amounts of bilingual data, which allows them to learn the relationships between words, phrases, and sentences in the source and target languages.

NMT models have several advantages over previous machine translation approaches. They can consider the context of the entire sentence to produce translations with improved grammar and naturalness.

AI Assistant

AI assistants in machine translation enhance usability by using AI technology. It performs language detection, context analysis, quality assessment, and real-time translation tasks to improve the translation experience.

Crowdin AI Assistant app leverages OpenAI’s ChatGPT API to serve as a co-pilot for translators. One of its significant uses is functioning as an MT engine. It supports over 100 languages, provides suggestions, and answers queries, increasing translator productivity.

You have various configuration options, including implementing Prompt Engineering for pre-translation tasks. Moreover, you can create a customized model. Choose the fine-tuning feature during the setup of Crowdin AI Assistant. Next, select the translation memories (TMs) and glossaries you want to employ for training and proceed to submit the training request. Crowdin will provide an estimated training cost. You can submit the request again if the price aligns with your budget.

Upon completing the training process, a trained model based on your selected resources will be accessible in the model’s section.

AI assistants optimize the pre-translation phase by adding translations to the text. After this, translators can edit the text. To see how AI can assist in pre-translating your project, watch our demo video:

Price: Detailed pricing from OpenAI.

Crowdin does not add any additional charges. Your payment is exclusively based on the rate established by OpenAI, depending on your selected AI model. The overall cost depends on the quantity of tokens you utilize, considering factors such as language, word length, and content.

To determine the token count in your text, you can employ OpenAI’s tokenizer tool.

Which Content Types Perform Well with Machine Translation?

Survey Localization

Combining machine translation with Crowdin’s localization platform offers an exciting approach to localizing surveys. The Typeform and Crowdin integration allows you to synchronize the forms you want to translate from your Typeform workspace. After completing the translations, you can effortlessly sync the translated forms back to your Typeform workspace. Then, the Machine Translation engine can translate the answers, so they can be collected in one place and analyzed regardless of the client’s language.

E-commerce Localization

Most e-commerce websites have hundreds of product pages, so using machine translation for less critical important content might be a good idea. You can review essential pages during e-commerce localization on a tight budget. For example, the Shopify translation connector in Crowdin allows you to seamlessly upload your content for translations from and to your Shopify account.

Subtitle Localization

Users can upload subtitle files into Crowdin using connectors with video-hosting platforms, like Wistia, for example. These files contain the original subtitles that need translation. After translation, proofreaders or subject matter experts can review the subtitles to ensure linguistic accuracy, adherence to guidelines, and cultural appropriateness of subtitles localization.

Chat & Email Translation

Machine translation can be a good assistant when it comes to live communication. Your support agents won’t have the luxury of sending each customer’s email to the translation agency. Typically, they would copy the message and paste it into DeepL or Google Translate. But that means losing precious time and additional work.

To save that precious time, we encourage you to try Crowdin’s translation assistant, which will build the MT of your choice into your chat or email provider. This way, your support agents would get instant Mt translations for customer inquiries via chat or email. The same goes for the responses. Crowdin translation companion can help you to translate tickets and live chats in real time.

Multilingual Knowledge Base

If you have hundreds of support articles, it might become a long-term project to localize all of them. That’s why we suggest you order translations from an agency for the core articles and consider MT for the others. Of course, post-editing would be a good idea here. Take a look at the Help Scout+ Crowdin integration to see how you can automate the translation of your help docs.

Crowdin’s Integrations with Machine Translation Engines

Crowdin integrates with the most popular machine translation engines, such as Microsoft Translator, Google Translate, Google AutoML Translation, DeepL Translator, Watson (IBM) Language Translator, and Amazon Translate.

Check out more machine translation engines that Crowdin integrates with.

In Crowdin, you can connect multiple MTs to your account, so you can use different MTs for different languages or content types. Here’s an article on how to connect MTs in Crowdin.

Machine Translation vs. Human Translation

Machine translation offers speed and cost-efficiency but may lack accuracy, context understanding, and cultural nuance than human translation provides. While machine translation can be suitable for specific tasks and content, human translation remains essential for high-quality, nuanced, and specialized translations that require a deep understanding of language and context.

Combining the strengths of both approaches, such as using machine translation as a starting point and then having human translators refine and polish the output, can often yield the best results.

How to Choose the Right MT Engine?

Choosing the right machine translation (MT) engine requires considering key factors:

  • Clearly articulate type of the content you need to translate, your translation requirements, including the target languages, the content volume you need to translate, and the desired quality level.

  • Consider whether you need a general-purpose MT engine or one specialized for specific domains or industries.

  • Explore engines offering customization to improve translation quality and domain-specific accuracy.

  • Check if engines handle anticipated translation volume.

  • Test pricing models based on usage, subscriptions, or custom options.

  • Conduct trials with different engines to compare performance and suitability. Learn more about comparing the best MT engines for your purpose.

-Seek user insights, reviews, and case studies to inform decision-making.

To Use Machine Translation or Not to Use

Machine translation technology can reduce the cost, efforts, and time spent on translation. On the other hand, incorrect usage can result in poor quality. So, try giving your MT as much context as you can. Either by uploading your Glossary and training the machine or using the AI Assistant in Crowdin - an app that requires no technical skills to set up, but it still can use your Glossary and understand the context of the content it translates.

Using MT is not something every project needs, but if you can benefit from it - why not give it a chance?

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Yana Feshchuk

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