Machine Translation Best Practices To Get Acceptable Translation Quality
Smart companies are automating as many of their processes as possible. This includes turning to machine translation (MT) tools for their localization projects. MT is an excellent way to get fast, cheap translations, but there are a few machine translation best practices you must take into consideration.
1. Quality Machine Translation Must Be Supported by Translation Memory
Machine translation has been around for nearly half a century, yet the general public only learned about it 11 years ago when Google Translate was launched. Today, according to Google, over half a billion people use Translate, and it has shown marked improvements in recent years.
However, no matter how smart Translate or any other machine translation technologies become, they cannot automatically account for subject matter, branded content, cultural issues, formatting considerations, terminology preferences, and other important aspects of translation.
To account for all of these factors in an audience and company-specific fashion, professional translation services get the job done by using a multi-step process featuring pre-planned considerations, review, and quality control.
Organizations who want results that are top quality will need to partner with a language service provider (LSP), even in this exciting time of machine translation innovation.
LSPs are able to supply a broad range of solutions that can be personalized to the needs of your project. For instance, one of the machine translation best practices that we use is to always couple this technology with translation memory (TM) software for added accuracy and speed.
TM is a database that captures a project’s translations for future use. All previous translations are accumulated in the database and reused for the same sentences or phrasing. The larger the database, the faster future translations will be.
The Globalization & Localization Association (GALA) goes into more detail about how TM works with MT.
2. Machine Translation Must Account for Unique Preferences
Following Google’s lead, several of the world’s other top search engines, including Baidu, Yahoo, Yandex, and Microsoft, have come out with their own MT services. Yet, Translate and all of these other services fail to take into account the user’s unique needs.
Our translation memory software makes it easy for us to set very specific parameters for spacing, capitalization, terminology, and more based on the context of your translation. This will help streamline the process and avoid continual edits.
Of course, when the translation is guided by a human hand and not based solely on a machine’s interpretation, then you have the flexibility to update antiquated source material into a target language that is modern.
For instance, it used to be quite common for materials to only use masculine general pronouns, but these days, in many cultures, that would be considered offensive. With dynamic TM, you can ensure your translations have inclusive gender neutral pronouns.
3. Set and Redefine Your KPIs
KPIs, or key performance indicators, are the metrics by which you measure the translation quality. You should set a series of standards for how accurate you expect your translations to be. And, these standards could vary based on the type of source material.
For example, you probably would not care if the translations for blog comments from irrelevant posts from years ago are particularly accurate. In cases like this, the KPIs may be less stringent, and a hands-off machine translation may get the job done.
On the other hand, when translating legal documents, such as terms and conditions, precise wording is crucial. Therefore, you will want to be sure that performance goals are met, so you can avoid getting into legal hot water.
A popular framework for describing the quality metrics of a translation is QTLaunchPad’s Multidimensional Quality Metrics. It evaluates quality based on several dimensions depending on the specific materials you are translating. We can also help you craft your KPIs.
4. Human Reviewers Ensure Accuracy
As mentioned above, the most affordable, accurate, and fastest translations involve a combination of human and machine translation. An expertly-tuned MT approach might better suit your project needs.
We have alternatives that incorporate various levels of software training inputs balanced with heavy or light post-editing. Essentially, for our more dynamic translations, we blur the lines between translations by machines and humans.
While many LSPs bristle at the idea of machine translations, we embrace MT as another tool to improve translations. However, for best results, we use professional translators to review the translations and make sure they are meeting KPIs.
Reviewers can take your corporate style guide and brand and make sure the resulting translations are in line with your other corporate communications in other languages. Machines are not able to factor in your products, clients, and organization when translating. The review process solves the problem.
When you follow these machine translation best practices, you can avoid many of the pitfalls that a purely automated process is susceptible to.