Best Practices for Translation Services – Triple-Pass Methodology

The main idea of triple-pass methodology began with our data entry and transcription services. In an effort to ensure the highest levels of accuracy and quality control throughout our processes, we implemented a quality assurance strategy where one transcriptionist or data entry operator completes a set of work and proofreads it, then the same work is forwarded to an independent reviewer who goes through it again. Hence the name, triple-pass. Each project is reviewed twice by the first transcriptionist or data entry operator, and then once more by a reviewer. 

This triple-pass methodology is a solid baseline approach to assure quality in a wide range of projects. It is certainly not our only approach to quality assurance, but whenever human beings are working and there is a human error possibility, this is one great way to minimize the risk of that happening. 

In other blog articles we will look deeper into some of the smart ways Capital Typing has integrated triple-pass methodology with other quality assurance strategies, because to make this approach as effective as it can be, we need to isolate the possibility of human error and make it as small as possible. But the article you are currently reading is about how triple-pass methodology in transcription and data entry became the inspiration for what we call Triple-pass Language Translation. 

We found that triple-pass methodology helps us manage collaboration in the translation team. We have a native speaker in the source language working together with a native speaker in the target language, in a manner very similar to the triple-pass system we brought in from other services. 

How it works is that the native speaker in the source language starts the process of translation. His main function is to ensure that the full meaning is captured from the source language. So notation is used to clarify idioms and challenging nuances of meaning, which a non-native speaker may miss. The native speaker translates into the target language to the best of his ability but the role of the notation is to flag the need for a conversation with the reviewer, who will be a native speaker in the target language. We use the notation flagging mechanism to organize the collaboration process, creating in effect a triple-pass process: the translation is done first by the linguist who is native in the source language, then reviewed, in consultation, with a second linguist, native in the target language.

This approach is one of the reasons why language translation from Capital Typing produces such high quality results. Our translations are more accurate because we have studied and perfected the process of translation. As with all of our services, we have studied language translation systematically and designed smarter language translation services, to better serve our clients.

Another important benefit of triple-pass methodology in language translation is that it supports the vital translation memory function, which helps us standardize the style of how the content is written in our translation projects. 

One of the challenges with language translation is that there can be multiple correct ways of translating something. Translation is as much art as it is science. The personal style and character of the linguist will naturally come out in the way the translation is done. This brings a challenge when we are trying to standardize results, especially in a big project where multiple translators are needed in any given language in order to handle the volume of work. Translation memory software is the best tool for dealing with this challenge, because it sets up a central database of rules for how specific words and phrases should be translated throughout the project.

We have integrated our triple-pass methodology into the translation memory system, so that now our collaboration between the source language native speaker and target language native speaker informs the translation memory database each time. Now, teams are working together, with true collaboration across the entire project, no matter how big the project. We have actually turned the challenge into an advantage, because now we get new ideas from each linguist, and ongoing consultation back and forth to keep improving the central translation memory. The software handles updates automatically so these conversations are fast and decisions are put into effect instantly.