The art of refining machine-translated text into a masterpiece of linguistic precision involves a human post-editor meticulously reviewing the machine translation (MT) output, meticulously correcting and enhancing it to achieve a level of quality that rivals human-translated content. Meet machine translation post-editing (MTPE).
In this comprehensive exploration of the subject, we will delve into the process, best practices, benefits, and challenges of post-editing machine translation.
What is machine translation post-editing?
Machine translation post-editing (MTPE) is a process in which human translators review and improve the output generated by machine translation systems. The goal of MTPE is to enhance the overall quality and fluency of the translated content, ensuring that it meets the desired level of accuracy and naturalness.
The process explained
Initially, an MT system translates the source text into the target language. This is an automated process where algorithms analyze the input and generate a translation based on predefined patterns and models.
Following the MT, a human translator (post-editor) reviews and edits the output to correct errors, improve coherence, and enhance the overall quality of the translation. The post-editor compares the machine-generated translation to the source text and makes necessary adjustments to ensure accuracy, fluency, and adherence to specific style or terminology requirements.
When do you need machine translation?
Businesses and translation professionals typically use machine translation when they need to translate a large amount of text quickly. MT can be much faster than human translation, so it is a good option for projects where you have a tight deadline.
Utilizing translation machine systems has the potential to reduce translation delivery times by an average of 50%, while also leading to a decrease of 20–30% in updates for translations. (Reinke, U. (2013). State of the Art in Translation Memory Technology)
MT and MTPE can also reduce the cost of translation. The two are far less expensive than human translation, which is great for businesses with a limited budget. Alas, you may need a translation that is accurate but not necessarily perfect. MTPE can nonetheless improve the accuracy of machine-translated text.
According to a survey from Unbabel, 39% of responders stated that they incorporate machine translation into their localization strategies. Among these users, 83% express satisfaction with the quality of the generated translations.
When not to use machine translation
Do not use machine translation when you need a translation that is highly accurate and idiomatic. Machine translation is not as good at capturing the nuances of language as human translation, so it may not be the best option for documents that require a high level of precision.
If you require a translation that is confidential or sensitive, machine translation may not be a good translation option to consider. It can be a security risk, as the machine translation engine may store the source text and use it to train its models.
Finally, machine translation is not as good at producing creative or persuasive writing as human translation. Marketers may find that it is not the best option for marketing materials or other types of creative content.
Improve your localization processDiscover an easy to use and afford localization app.
Challenges of post-editing machine translation
Machine translation has come a long way in recent years, but it is still not perfect. There are a number of common mistakes that MT systems make, which can result in inaccurate or unnatural-sounding translations. These include things like:
- Omission of words or phrases. Sometimes, MT systems will omit words or phrases from the source text, which can change the meaning of the sentence.
- Addition of words or phrases. Conversely, MT systems can also add words or phrases to the source text that are not there.
- Errors in grammar and syntax. MT systems can also make mistakes in grammar and syntax, which can make the translation difficult to understand.
- Errors in meaning. Occasionally, MT systems will completely misinterpret the meaning of the source text.
- Literal translation.MT systems often translate words and phrases literally, without considering the context of the sentence. This can lead to translations that are nonsensical or grammatically incorrect.
- Difficulty with translating sarcasm and humor. MT systems often struggle with sarcasm and humor, as these rely on context and cues that are difficult for machines to understand.
- Difficulty with translating technical or specialized language. MT systems may not be able to translate technical or specialized language with the same accuracy as general text.
Best practices for machine translation post-editing
Machine translation post-editing plays a crucial role in refining the output of machine translation systems to meet specific quality standards. Here are some best practices to consider when editing your translated content:
Understand the goal
Is the translation intended for informative, promotional, or technical purposes? You need to gain a nuanced understanding of the document’s context, industry-specific terminology, and the purpose of translation.
Employ high-quality source text
In order to avoid complex sentence structures, jargon, and technical terms that may be unfamiliar to MT engines, your source text needs to be easy to understand. You will also need to ensure the source text is free of grammatical errors and spelling mistakes, as these can also hinder MT accuracy. Maintain consistent formatting throughout the document, including font styles, paragraph breaks, and spacing.
Provide reference documents and glossaries
Provide relevant reference documents and glossaries for technical or specialized content to aid post-editors in understanding specialized terminology and concepts. Access to comprehensive reference materials can significantly improve the accuracy of translations in specialized areas.
Encourage collaboration among post-editors
Encourage post-editors to share their knowledge and best practices to improve the overall quality of translated text. You can leverage the combined expertise of post-editors to resolve complex translation issues and develop effective strategies.
Asses the quality
Scrutinize the machine-generated content for errors at various levels, including syntactic, semantic, and stylistic errors. You will need to address mistranslations, omissions, and structural issues. Also assess the natural flow of the translated text. Make sure that the sentence structures are not only grammatically correct but also maintain a coherent and natural progression, enhancing overall readability.
Use CAT tools to establish and maintain a consistent glossary of terms throughout the document. Check that the key terms are translated consistently, promoting a cohesive and professional final product.
Consider cultural sensitivity
To adapt the content to different cultural nuances, you will need to go beyond literal translation. This involves understanding idiomatic expressions, cultural references, and appropriately modifying the content to resonate with the target audience.
Machine translation post-editing can be significantly enhanced with the use of various tools and technologies. Some commonly used tools include computer-assisted translation (CAT) tools, translation memory (TM) systems, terminology management tools, QA software, just to name a few. Or you can use a translation management platform like POEditor, that incorporates many of features of the aforementioned tools.
Continuously evaluate MTPE performance
Conduct regular evaluations of MTPE performance using metrics such as accuracy, fluency, and style to identify areas for improvement. One way to do that is to collect feedback from stakeholders and users of translated content. Afterward, use feedback and evaluation results to refine MTPE processes.
Machine translation post-editing offers a transformative solution that seamlessly blends the speed and efficiency of machine translation with the expertise of human translators. By combining the best of both worlds, MTPE enables businesses and organizations to bridge cultural divides, expand their global reach, and communicate effectively across borders.