Best Practices for Machine Translation Post-Editing (MTPE)

The professional translator community around the globe is vast, comprising roughly 640,000 individuals. Translation is necessary for various industries, making machine translation post-editing (MTPE) services more critical than ever. What is MTPE, and what are the best practices for it?

CCC International will discuss everything you need to know about this process and why investing in machine translation post-editing services is essential for businesses everywhere!

Key Takeaways:

• Machine translation is an automated method of converting text from one language to another, offering the benefit of fast and large-scale translations; however, it often presents the challenge of lacking cultural and contextual nuances.
• Machine translation post-editing is having a human translator review and correct the output from machine translation to improve accuracy, consistency, and fluency.
• Investing in machine translation post-editing services or MTPE services allows businesses to reap the benefits of machine translation while ensuring accuracy and quality as you would with any human translation.
• Translation, editing, and proofreading or TEP services provide the best of both worlds if done correctly, so it’s best to partner with a professional translation services provider.

Table of Content:

• What Is Machine Translation?
• Types of Machine Translation
• MT Benefits and Challenges
• What is MTPE?
• The Importance of MTPE
• Best Practices For MTPE
• CCCI – Professional TE, TEP, and MTPE Services

Machine translation (MT) explores using software to translate text or speech from one language to another. It enables users to break down language barriers and communicate effectively, regardless of their linguistic background.

Machine translation is common in various industries. For instance, global corporations use MT to translate business documents, websites, or customer service interactions to reach a broader audience. In the legal field, MT can help translate legal documents quickly. Media companies often use machine translation for subtitling and dubbing foreign content.

Note: The counterpart to machine translation is human translation, a process carried out by professional linguists fluent in both the source and target languages.

The evolution of machine translation has resulted in various kinds of machine translation systems, each possessing unique advantages and shortcomings. Primarily, we can classify machine translation into three types:

Historically, the initial iteration of machine translation, rule-based MT, heavily depended on a large set of predefined linguistic rules. These rules assisted the software in conveying the meaning of the text from one language to another. However, the output quality was generally low, and the process necessitated the manual inclusion of languages and substantial human post-editing.

Statistical Machine Translation (SMT) enhances the translation process by constructing a mathematical model that identifies correlations between words, phrases, and sentences within a specific piece of text. This model is then applied to a different language, facilitating the translation of these elements. Though it represents an improvement over the rule-based MT, it’s full of similar challenges.

Neural Machine Translation (NMT) employs Artificial Intelligence (AI) technology to mimic how the human brain learns and processes languages. Rather than strictly adhering to a predetermined set of rules, the neural network within the MT engine takes on the task of encoding and decoding the original text. This approach enhances translation accuracy and streamlines the inclusion of additional languages.

Machine translation offers several significant benefits, including the following:

• Speed: Machine translation can translate large amounts of text faster than a human translator. This speed is invaluable when quick translation, such as customer service interactions or news updates, is necessary.
• Efficiency: MT is an automated process that can work non-stop and handle numerous projects simultaneously. The efficiency is particularly beneficial for businesses that require consistent, high-volume translations.
• Scalability: Machine translation can quickly adapt to the volume and complexity of translation tasks, making it scalable for varying business demands.
• Accessibility: Machine translation breaks down language barriers, making content accessible to international audiences. This accessibility helps businesses expand their reach and engage with diverse customers.

It’s also important to note that while machine translation provides numerous advantages, it may not fully grasp cultural nuances and context the way a human translator can. Here are some of the challenges:

• Accuracy: MT is still a work in progress, and it’ll take time before it can accurately capture the nuances of language. As such, automated translations may not convey the intended meaning or tone accurately.
• Grammar and Syntax: Machine translation often struggles to generate appropriate grammar and syntax, making the output difficult to understand.
• Cultural Context: MT doesn’t always recognize cultural differences and regional variations in language, which can lead to misinterpretations and misunderstandings.
• Human Intervention: Since machine translation is still evolving, it requires human intervention or post-editing to ensure the accuracy and quality of translations.