New reports forecast growth of the machine translation market at nearly 25 percent in the next four years, with technological improvements likely along the way. With such expectations, It’s tempting to believe computers will soon perform professional document translation services well enough that there soon will be no need for human translators.
But Jeremy Coombs, senior vice president of operations at MultiLing, shares why he believes it’s not time yet to give up on humans in the near future. In an article for the GALA blog he outlines how humans who specialize in their native languages, cultures and fields of expertise still need to be involved in the majority of translations, even while technology such as machine translation plays an important role in making valuable content in one language accessible to all.
“The need for and value of human translators is especially true for intellectual property, particularly patent applications, where even one mistranslated word can result in invalidated patents and millions of lost revenue.”
While everyone rushes to have valuable content to attract online business, the question of how to best prepare – or create – that content for translation is important to consider. EContent magazine addressed the topic in an article today by Michael LoPresti: Preparing Your Content for Machine Translation. Kevin Nelson, senior vice president of strategy and technology at MultiLing, provides for the article some important insights on how to get the best translations a machine has to offer:
“If you keep the realm narrow, and you keep content you’re creating within that same realm, you’ll have a lot better chance of getting good content. This is part of the big difference between what you get when you use Google Translate, as opposed to using a specific server that is trained for your material. Google is really working on being the translator for the world, but it’s still a ways down the road for it to get there. To hand your content to a translator as vast as that, the odds are that it hasn’t seen enough content that’s related to your industry yet, and the output won’t be quite up to business standard.”
MultiLing has a long history of adopting technology for more consistent and efficient translations – leading to the high quality translations that our clients depend on.
For more tips on preparing content for translation, read the full EContent article here.
Last month, Google Translate celebrated its 6th birthday. According to Google, more than 200 million people use this simple Internet translation service monthly. “What all the professional human translators in the world produce in a year, our system translates in roughly a single day,” said Google Translate engineer Franz Och, who originally invented this Google service.
In 2010, the US Defense Department spent nearly $ 700 million on a single translation contract for human interpreters – mostly in Afghanistan. A high demand for machine translation systems that would reduce this vast budget is obvious. Continue reading →
Machine Translation is becoming an increasing issue in the worldwide patent industry. In a landmark step towards increased use of worldwide patent information on the internet, the Commissioner of the Japan Patent Office (JPO), Yoshiyuki Iwai, and the President of the European Patent Office (EPO), Benoît Battistelli, have signed an agreement on 6 February 2012 which will provide users of the patent system with better machine translations of patents from Japanese into English and then into German and French. The agreement significantly enhances the scope and quality of Espacenet, the public patent information service on the EPO website, by adding an automatic translation tool. Continue reading →
The World Intellectual Property Organisation (WIPO) recently launched an online machine translation tool. It allows users to translate the titles and abstracts of inventions from English to French and Chinese and vice versa. Other language pairs, notably Korean-English and Japanese-English are being studied. The tool is a WIPO in-house development using Moses open source technology and has been specifically trained with bilingual corpuses of text from the patent field, taking account of the International Patent Classification (IPC). Continue reading →