When searching for solutions that will help businesses with multilingual communication, companies inevitably turn their attention to machine translation services. Although by all accounts it appears to be a good investment, the use of machine translation might trigger significant concerns on the part of some users. Today we will explore the common assumptions and fears about MT, evaluate their reasonability, and shed light on recent developments in the field.
Machine translation can lack accuracy
Considering the innate complexity of languages, multiple grammar rules and contextual nuances, mistakes are bound to happen occasionally. However, most businesses shouldn’t worry about that score, as today’s neural machine translation is developing rapidly. In 2020 it was estimated that neural translation engines were capable of instant text translation with 60-90% accuracy. Linguistic experts claim that every year it improves by 3-7%. The gap between human and machine translation might seem significant, but here’s the deal: various surveys have shown that people prefer to interact with information in their own language, even if it’s poor quality.
People look for value and familiarity, and even with imperfect machine translation they are more likely to visit your site, make a purchase, read your blog or write a review. If your client or partner speaks a different language, but you are still able to understand most of what is written or spoken, you’ve got a greater chance at solving any problem easily. If you need a completely accurate translation, the quickest and cheapest thing to do is first to translate the text using machine translation software and then ask a proofreader to eliminate any uncertainties in the text.
Robots will replace humans
Many doomsayers have predicted that the arrival of machine translators will replace human translators for good. However, completely the opposite happened. Rather than replacing human translators, machine translation has been aiding them by handling straightforward, mundane translation tasks, allowing professionals to focus on complex texts that require deep cultural and contextual understanding. The market of translation has been growing exponentially since the 1990s with the arrival of statistical machine translation and improvements in computing power. Now, professionals can tackle more tasks than ever before in shorter periods of time. As for people who decide to use machine translation tools by themselves to improve their business, they can always ask a company that provides MT solutions to train their translation models to suit specific linguistic needs.
Sensitive data can be leaked
Sensitive data leakage is a valid concern when using machine translation services, especially in an era where data breaches frequently make headlines. If the machine translation software you chose sends your data to a cloud service, it can lead to potential safety breaches, as your data gets processed by third parties. As businesses can not simply create their own machine translation tools and the services of a human translator can be very costly and time-consuming, they have no other choice but to trust somebody else, which can cause a problem. The only safe way out is to use on-premise solutions, like Lingvanex On-Premise Translation Software, where all of a company's data is stored and processed within its own infrastructure, working offline, without any need to use other services. In this case, companies control both the costs and the safety of their translation.
Not all languages are represented
According to a famous reference publication Ethnologue, there are over 7,000 languages worldwide, and you’ll be hard pressed to find a machine translation service that accommodates them all. Several prominent machine translation companies now support over 100 most frequently spoken languages. The training of one translation model is a complex process that requires a lot of expertise, data and time. In the early days, only huge companies could have both the computational power and human resources to do it. However, with the advancements in the AI world, it becomes more accessible for all machine translation companies to train new language models or improve existing ones. Many companies, for example Lingvanex, work very closely with their clients and when the case demands it, they help their clients to adjust machine translation services to their needs.
Machines can’t translate real time communication
It might have been true several years ago, when the technology has often struggled to deliver accurate translations at the pace of a normal conversation. Now, however, advancements in the field of natural language processing and machine learning allow companies to receive complete translation in the space of seconds. If businesses desire to have complete hold of their translation processes and minimize latency, the best solution would be to install a machine translation server on their own premises. Lingvanex On-Premise Translation Server and Voice Recognition Server can process more than 2 billion characters a day, which equals around 645 Bibles, with topmost speed and a potential for scalability. With it, you receive a reliable tool, promising near-instant translations that could revolutionize how businesses communicate across language barriers.
Conclusion
Despite initial concerns about the technology of machine translation, it has evolved over the recent years and has successfully addressed many of them. Machine translation remains a key tool for enabling international communication and business collaboration. With the development of neural MT methods many fears have diminished significantly as the quality of MT has increased greatly. Even imperfect machine translation can boost international interaction and benefit businesses in a secure and effective way. MT technology has now established itself as a tool for assisting human translators, rather than completely replacing them.
