Artificial Intelligence is changing the translation industry. But will it work? AI has infiltrated numerous aspects of our lives in recent years, thanks to improvements in the field of machine learning, where computers ostensibly program themselves. One of the most widely-discussed advances has been the use of AI in translation. The technology works by recognizing words individually and then, takes advantage of the fact that relationships between certain words… are similar across languages to create its translations. Even though it has already found its way into a number of our most commonly used websites and platforms – but just how reliable is the technology?
How AI is breaking the language barrier. There is every chance that we have already seen AI translation in action, whether on Facebook feed or through browsing international pages in Google. Microsoft Translator App which not only translate text, but also speech, images, and street signs. The AI takes the context of an entire sentence into consideration, making for much more accurate results. The translation function also allows the neural network to update in real time through user input.
AI translation has its limitations. One Google researcher noted that “People naively believe that if you take deep learning and…1000 times more data, a neural net will be able to do anything a human being can do, but that’s just not true.” Despite its rising popularity, AI translation is not quite there yet compared to experienced human translators.
A recent contest in South Korea pitted machine translation tools against a team of professionals in translating two texts from Korean to English and vice versa. The result of the 50-minute test revealed that 90% of NMT (neural machine translated) text was grammatically awkward, or definitely never the kind of translation produced by any educated native speaker. Likewise, the translation functionality of the highly touted wearables Google Buds seemed like a damp squib on their release, with reviews noting that they were “too awkward and imperfect to be of much use.” While an instant translation may be useful on the go, a company translating their website, for example, should have their entire site translated by human experts rather than machines. Online translation services do not allow for easy accommodation of text expansion. While your website might look ideal in English you may need to create an entirely different basic visual outline of your page in order to accommodate longer words and sentences. Still, apart from its new technology features, there is much to be developed, especially when it concerns accuracy to the Portuguese language. Here is an example of the many problems found (Portuguese-English). Multiple Meanings: Machine Translate: The phrase “The table is red” = “A tabela é vermelho”, or still “A mesa está vermelha”. In the first Portuguese example, despite the gender mistake (it should be vermelha), and the table could be an object, not necessarily a table of columns. Some machine translation platforms gives us an option for changing “a tabela” to “a mesa”, but why does it choose a table of columns in the first place? I think table as a furniture object is much more common. In the second Portuguese example, wrong verb “está” (it should be “é”).
European Portuguese: Google Translate is Brazilian, but it should offer an option for other dialects. Many students that are learning European Portuguese, do apply Brazilian sentences because of Google Translate, which are useless for them. Observe the following example: Google Translate: “I want to talk about a fact” = “Eu quero falar sobre um fato”. European Translation: “Eu quero falar sobre um facto”. The word “fato” means “suit” in Portugal. So basically if you speak like a Brazilian, the same phrase in Portugal will mean. “I want to talk about a suit”.Is there an artificially intelligent future for translation? Until AI can be accurate as a human translator, a platform like Unbabel, could provide a workable future for machine translation. With assistance from human translators, who can not only correct but help teach them in a way that machines cannot teach themselves. AI translation could find itself on the right track. For now however, the technology is arguably not yet fit for purpose on its own.