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Language translation in the global age

Most business and technical people all over the world are fluent in English. With globalization and communications technology spreading standards and uniformity, the natural expectation would have been for the English language to marginalize the usage of national languages in business. Yet globalization has brought along an unlikely companion: localization. While small companies from any place aspiring to cater to a global clientele have had to embrace English in order to put themselves on the economic map, larger companies, already operating on an international scale, have discovered that huge markets can be opened and penetrated more efficiently by embracing local languages in marketing and distribution. Today, the field of language services is a dynamic and competitive one, both for human and for automated translation. In 2005, the global market for human translation was well over $1 billion US. But in the last decade, the exponential growth of content needing to be translated can no longer be handled by the slow and costly (albeit high quality) process of translation by humans. E-commerce and globalization of the economy are major factors pushing the field of automated translation forward. So is the collaborative nature of work in many sectors, where people who are not proficient in each other’s language must work together in innovative and productive ways. The growing mobility of the general population is another factor, as are political developments, such as the expansion of the European Union (where official materials must be available in all the languages of the 27 member states); the creation of new European states after the fall of the communism; support for minorities and multiculturalism in North America; and last but not least, military operations around the world have resulted in the need for dramatic volumes of information to be translated. Machine Translation (MT), a scientific discipline at the intersection of linguistics and computer science, goes decades back in history. Currently, there are many corporate, government and academic laboratories dedicated to the advancement of the discipline beyond research, experiments and demos. Machine translations are still not perfect in style, grammar, or even semantics, but they are fast, cost-effective and useful for domains using highly standardized text (i.e. technical or legal), and in any settings where the presence of a human translator is just not practical. The commercial use of automated translation is still lagging behind the technology. Yet the direction in which automated translation is being pushed by researchers is remarkable. Two inventions from IBM illustrate this: • The head-mounted display content transformer (filed for patent in the US in 2006): This device looks and acts like a pair of “magic goggles,” where users will be able to see inscriptions in a foreign language such as Hebrew, a language with an alphabet totally different from the Latin one, translated into English. This invention is also aimed at helping people with learning disabilities by simplifying the text they see, or helping those with colour blindness by “translating colours.” • The multilingual Automatic Speech-to-Speech Translator (MASTOR, the product of several years of research at IBM): This software helps people who do not understand each other’s language have conversations in real time. For now MASTOR is proficient with English and Mandarin, and is “learning” Spanish and Arabic. MASTOR will be able to run on various platforms, such as pocket PC or cell-phones, as well as fixed stations in airports and other places where people are likely to need this type of service. The commercial use of automated translation will no doubt be helped by the mainstream technologies of wireless communications, hand-held computers, cell-phones and ipods. But it is survival of the fittest. Sometimes similar ideas emerge at competing companies. For example in 2002, Hewlett Packard labs came up with the now passé HP Jornada, a hand-held PC able to translate text based on optical images, much like IBM’s proposed head-mounted device. Automated translation is based on incredibly complex algorithms and require huge computing power and speed in order to deliver reasonably accurate translations in real-time. Most anticipated applications are related to interaction of people in a global work setting (international teams, missions in remote parts of the world where translators are not readily available), in tourism or for entertainment purposes (real-time subtitles in television – think stations such as Al-Jazeera). Another potential use is voice-control of appliances and cars. It remains to be seen whether attempts at commercial usage of these or other inventions in the automated translation field are going to become popular and profitable. While research has come a long way, commercial deployment is still a moving target.