The Role Of Machine Translation For Global Businesses

Machine translation has been making headlines – but for the wrong reasons. Recently, a tweet from Google Translate was accused of making sexist assumptions about gender-neutral language and went viral. Elsewhere, when Amazon used its own automatic translation technology to launch its first ecommerce site in Sweden, it outputted lewd and vulgar translations, bringing attention to the launch for all the wrong reasons.

Yet, despite the obvious limitations of the technology, UK-based translation provider The Translation People has experienced a 2,016 percent increase in the volume of work it carried out with machine translation, while website enquiries for this service increased 1,130 per cent.

There are benefits to the technology, including significant time and cost-saving efficiencies for international businesses. But recent examples of the inaccuracies that can occur might be a cause of concern for many. In reality, the technology can only provide the most accurate, effective and creative translations when delivered as a hybrid solution together with human translators.

Machine translation centres on processing input and producing output. Words, sentence structure, subject and grammatical information are all analysed after input then translated into the desired language. But the accuracy of the output is determined in large part by the size of the language database sitting behind the machine. The more bilingual material fed into the engine by base engineers, the better the result will be.
 

 
Another factor that affects quality is the type of text, as some content types work better than others. Direct and straightforward language– such as that found in instructions and user manuals – is well suited to machine translation; emotive copy or complex language, less so.

To achieve the highest quality results, customised engines should be developed for individual companies. An assigned language expert can train the engines over time, enabling the machine to understand the business’ style of writing, tone, nuances and industry jargon. If any element of a translation is incorrect, it’s spotted and edited by the translator. These edits can be used over time to train the machine not to make the same mistake again in the future, driving a continuous improvement in the output of the machine, achieving greater accuracy and achieving a more efficient process.

However, it would be wrong to assume that machine translation will be the most appropriate process for every scenario, because it isn’t suitable for every sort of text, or for every language combination. Instead, businesses should work with a translation provider that collaborates to understand the scenarios where machine translation would be a benefit, and where human input is more relevant.

They should assess your requirements to understand if spending several weeks or months nurturing a customised machine translation system with company specific terminology and language will generate translation efficiencies and lead to the business saving time and money in the long run.

Machine translation is going to become more sophisticated, but there is currently no universally agreed-upon or standardised approach to ensure accuracy across the board. Until that happens, it will always benefit from the expertise of a human translator. Placing humans central to machine translation will achieve a premium level of quality and potentially offer huge value to the client. Humans and technology may one day be on par when it comes to their language capabilities, but until then, people must remain at the heart of the machine translation process.

 

Written by Alan White, business development director, The Translation People