Until just a few years ago, machine translation (MT) was still a niche product. Nevertheless, companies are increasingly incorporating MT into the translation process in order to produce translations in a faster and more cost-effective manner. However, since machine translation still results in errors, post-editing continues to be essential in most scenarios.
In this article, we put our focus on the various types of post-editing and their differences. We explain how to successfully integrate them into the translation process.
It is only possible to get the full added value of machine translation if you combine it with post-editing to improve quality.
Translators and post-editors who specialize in this service and who have undergone appropriate additional training are responsible for post-editing in most cases. The skills that post-editors need to master are enumerated in the relatively new standard ISO 18587. Their qualifications include:
The errors that occur in machine translations vary depending on the system. Older rule-based systems generated very choppy translations with poor word order and inappropriate arrangement of clauses. The somewhat more modern statistical systems frequently produced incomplete translations with sentences that were grammatically incorrect. Last but certainly not least, the neural machine translation seen today requires that more attention be paid to content. These systems produce texts of a more stylistically sound and articulate character and have almost no spelling or grammatical errors, making it easier to overlook content errors, especially when they relate to terminology.
Regardless of the system used, it is always advisable to carry out post-editing, with the exception of a few narrow use cases. Depending on the requirements that the target text needs to meet, post-editing may not be absolutely necessary if translations are being produced for test purposes or to be distributed as simple brief posts on social media, for example. A distinction is generally made between light post-editing and full post-editing.
Depending on where the content is being used, the translated text needs to fulfill different criteria. Is the translation only needed in order to provide a general overview (to give a gist of the content) or is the translation to be published? Based on the requirements and applicable budget, either light or full post-editing can be carried out. With light post-editing, the post-editor only corrects major errors. With full post-editing, the resulting translation should be (close to) indistinguishable from human translation. TAUS has created a number of guidelines for the two types of post-editing:
Keep in mind that the quality of the raw translation can influence the decision regarding what kind of post-editing is ultimately needed. If the raw translation is already quite good, it is sometimes sufficient to carry out light post-editing in order to arrive at a high-quality translation.
If high-quality translations are absolutely required in your area, but you still want to use machine translation, a customized engine can be the right solution. As suggested by the name, these are machine translation systems that have been trained using the customer's own data, making it possible to deliver better raw translations. For more information, refer to the article "Machine translation for companies".
The quality of machine translation also depends heavily on the source text. If the source text contains numerous errors or the clauses of the sentences are nested in a convoluted manner, the MT system will have a hard time making sense of it. On the other hand, machine translation will do extremely well with standardized, short sentences containing factual content—such as texts from a business environment, operating instructions and user manuals, reports, and so on.
To increase the quality of the raw translation, pre-editing can therefore be a useful step. In this way, post-editing becomes faster and easier.
To include post-editing in the translation process, it is first necessary to implement the machine translation engine. This works best in combination with a translation management system in which the desired engine (DeepL, SYSTRAN, Textshuttle, PROMPT, KantanMT, Google Translate, etc.) can be connected via API. On this basis you create a pre-translation of the text, which is post-edited in the next step.
The clear advantage of this approach is that the post-editor then has access to all relevant content that is available in the translation management system. The key resources are the terminology database, the translation memory, and the quality management module. Why?
These three TMS components are essential for efficient post-editing, which is known to be all about speed (post-editors process some 7,000 words daily).
In theory, companies do not need a translation management system to use machine translation. Texts can be machine translated with the selected engine and then manually sent to the post-editors (such as by e-mail). However, this approach has a number of disadvantages.
, as internal company data are sometimes processed without any protection. Another important aspect is the efficiency during post-editing. If the post-editors do not have access to the respective technological functions (terminology database, quality management module, or translation memory), post-editing takes longer and requires more effort. For example, without a translation management system it is not possible to ensure reuse of previously translated sentences or use of corporate terminology.One of the main advantages of combining machine translation and post-editing in the translation management system is the quality management functionality. Quality criteria are integrated into the system on a centralized basis, allowing you to specifically define such criteria for your individual applications using regular expressions, for example. In this way, you can always enable the use of up-to-date terminology and automate processes. The result: Faster machine translation, faster post-editing, lower costs, and higher text quality.
You should therefore consider everything very carefully in advance and seek out advice on how you can use the technologies with maximum efficiency and
them if possible.Machine translation is no longer a technology in its infancy. While it will not replace human translation anytime soon, it is a good alternative that allows you to save time and money in some scenarios. However, translations produced by machines can rarely be used in their "raw" state.
Post-editing is a good solution for taking advantage of machine translation while maintaining a predefined quality standard. Whether light or full post-editing is needed depends on a variety of criteria that the company needs to examine in advance. Machine translation and post-editing have the biggest payoff when used in combination with a translation management system, which provides post-editors with important components that facilitate their work. In addition, it makes it possible for the company commissioning the translation to ensure that data protection requirements are met.
