Being a professional translator can be difficult. Many believe that translators simply “write” words from the top of their heads and call it a day. The reality couldn’t be farther from this notion however. Translators often spend hours on end trying to figure out single pages of industry-specific documents.
In that regard, translators come in many forms and range from book translators to technical and medical translation experts. However, all of them often need to use data science methods to determine whether or not they did a good job with their work.
In essence, data science represents the process of research through science in order to prove that something is right or wrong. This technique is often required in translation due to the nature of different languages with large gaps and margins of error in between. With that in mind, let’s take a look at some of the most common translation problems that can easily be solved with adequate implementation of data science.
- Urgency in decisiveness
Translation experts are often in charge of localizing documents for project managers and company executives. These individuals rarely have time or patience to read through dozens of pages of raw data without an explanation. In these cases, translators can implement data science in order to extrapolate the “gist” of the document they are working on.
It’s important to note that translators should always be objective in their work and never put their personal thoughts or feelings first. This is the opposite of being creative but it is essential for quality translation to be done correctly and without deviation. In short, translators can implement data science either themselves or through a third-party with expertise on the matter in order to “cut to the case”, so to speak.
- Unbiased localization
Localizing a corporate document can be extremely tough due to the technical language implemented within. Translators often improvise or take days to translate a single document because of the bureaucracy involved in their work. However, data science can be used to create unbiased localization for just about any language out there. Being unbiased about the work they do is one of the key postulates of professional translators.
Translators can often lose credibility and respect of their peers if they choose to tamper with the good will and trust of their clients. Research through technical literature, online resources and industry experts by implementing data science can be extremely helpful. Not every reader will be verse at the topic you translated for them so this presents the perfect opportunity to flex your data science muscles further.
- Too many numerals
Numerals, numeric data and other non-phrasal translation content is some of the most treacherous work out there. Translators are often required to present factual data as it is represented in the original language. However, the accompanying text and charts may not coincide with the data that the translator came up with in the end. It’s important to note that there are considerable cultural barriers between different overseas industries.
Something that seems logical in the US may seem ludicrous in Japan, China or even the UK. This is why translators are encouraged to implement data science in order to translate any and all numeric data they come across. It will allow them to double-check any translation work they may have done just to be sure of its correctness. They can also do some outreach and ask for help with some of the largest translation companies on the web. This also represents a form of data science since it involves working with other translation professionals.
- Niche phrases and lingo
There is nothing worse for a translator than to come across niche phrases or lingo unknown to those outside of it. Translators rarely specialize in particular niches for very obvious reasons. It lowers their income and choice of projects drastically.
This means that translators often work in an industry of choice without looking into the specifics of very narrow niches. However, this is where problems can come to fruition due to that niche’s lingo. Translators often face very difficult and hard-to-understand words even with their expertise and experience. Data science can help them determine what that particular word stands for and how it can be translated into a different language.
While the word may lose some of its “charm” in translation, it will become much clearer and understandable to a wider range of readers. This is also why content creators in general are advised to steer clear of niche phrases that may fly over people’s heads without proper context.
- Level the playfield
One of the greatest challenges a translator can face is to find the lowest common denominator in their work. Translating a document that everyone needs to understand (and that means “Everyone”) can be extremely difficult. Extensive research and fact checking is inevitable when working with this type of projects.
Data science can be one of the most effective tools in a translator’s arsenal if they come across one of these projects. They can use hard science, literature and professional scientists in their respective fields to lower the barrier for entry in their work.
This type of work is often commissioned by large companies and international enterprises with multiple overseas retail fronts. Finding the right language and choice of words that will be understood by everyone is often a Herculean effort on the translator’s part. However, these projects are also some of the most lucrative out there so there is an incentive for translators to take them up and work a little harder.
Data in translation
Using scientific methods and research might not be the type of translation that anyone would jump at. It requires meticulous and patient work that many writers are simply not up for. Try using data science in your next translation project before you write it off completely. While it may not be the most exciting or glamorous work, it will teach you a lot about different niches and how they cogs actually turn.