Linguist systems5/2/2023 ![]() ![]() Neural Machine Translation (NMT) seeks to replicate the thought process of a translator and work its way towards the result in a similar way to its human counterpart. However, by far the most impressive technological leap in machine translation was marked by the introduction of neural networks around the 2010s. Operating on a finite database of previous translations, the unpredictability of language and its propensity to encapsulate a wide range of nuances and meanings would elude the limited engine, and would thus cause it to drastically depart from the meaning of its source text.Īs such, companies began to develop a hybrid method that brought rules and statistical analysis together in an effort to increase the quality of their automated translations, to varied results. ![]() However, early adopters had to immediately contend with numerous flaws and errors. IT companies such as IBM introduced the use of statistical models and machine translation adopted the use of this novel technology, shifting away from the use of previous rule-based engines. The 1990s brought forth significant improvements in this field, with the advent of revolutionary computing technologies. Procedurally interpreting and translating text has been a topic of research from the 50s, and techniques for systemic language translation used by modern software can be traced as far back as the 9 th Century.Īt first, machine translation systems, developed for use in the Cold War, used rule-based methods, applying rules that have been developed by humans or sourced from dictionaries in order to achieve rudimentary translations. Machine translation is not, by far, a modern concept. Technology companies are constantly announcing breakthroughs in the development of AI algorithms, and have begun to perceive of a future when MT might even replace human translators.Īnd yet, as hopeful and exciting as this future sounds, how realistic is the expectation of entirely replacing human translators and how do the next 5 years look like in this rapidly evolving field? While translating tools that employ some sort of machine assisted translation have been around for many years, effectively aiding translators in streamlining their work, machine translation promises to revolutionize the field with the aid of AI. One of the proposed solutions for a far quicker, and more cost-effective method to localize is, of course, Machine Translation. ![]() The problem is that, even as they employ new and innovative technologies to aid in their work, the complex process of translation is a time consuming and highly specialized task that has up until now, been solely performed by human linguists. The global translation industry continues to grow with its role at the forefront of this trend of businesses seeking to break the constricting barriers of language in order to offer services and products worldwide. As the age of globalization and worldwide electronic communication is unfolding, companies are in a constant race to fulfill their ever-demanding needs for accurate and, more importantly, fast localization in a wide array of languages. ![]()
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