Being a translator or interpreter has been rated one of the 50 Best Careers of 2012, and reports suggest that careers in the Translation Industry will continue to grow over the next decade. Will that be the case though?
More than 11 years ago Ray Kurzweil – inventor, futurist and transhumanist, already predicted in his book “The Age of Spiritual Machines” that computers will reach a high degree of almost human proficiency in translating written and spoken language by 2029. For those of you who would light-heartedly rule out this prediction as slightly wacky here are some words about Kurzweil. He is the principal developer of the first CCD flat-bed scanner, the first omni-font optical character recognition, the first print-to-speech reading machine for the blind, the first text-to-speech synthesizer, the first music synthesizer capable of recreating the grand piano and other orchestral instruments, and the first commercially marketed large-vocabulary speech recognition solution. Quite an impressive list, isn’t it?
The State of Research in Machine Translation
Scientists and academics have been trying to automate translation for almost as long as computers have been in existence. In the 1940s and 1950s it was widely assumed that once the vocabulary and the grammar rules of a language had been codified, it would make automated translation easy. However attempts to make computers learn languages in this way over the next forty years were largely unsuccessful, unless the range of words they were expected to translate was very limited.
Then in the 1980s, computer giant IBM carried out pioneering research into the use of words in sentences. Its researchers examined the relative frequency of different groups of three words occurring in a sentence, which subsequently paved the road for the use of the statistical approach in machine translation – analysing bodies of text that have already been translated from one language to another. Put simply the computer doesn’t understand the languages or know any grammar, but might use statistics to determine that ‘dog the’ is not as likely as ‘the dog.’
In the 1990s, while Kurzweil was formulating his prediction, a young research scientist Franz Och started working on language translation algorithms. Today Och is the man behind Google Translate, which still is very crude but nevertheless has reached mainstream. Online services such as Google Translate and Yahoo! Babel Fish both use statistical machine translation techniques and are literally getting better as we speak.
The Quality of Machine Translation Solutions and Software
Can we use language translation software for business and academic purposes? Can machine translation replace human interpreters and translators? The answer is: sort of. Machine translated material still needs the human touch but definitely makes the job of the human translator easier and most importantly faster.
Today’s translation tools are built on the highest quality data compiled by the best translators in the field, and comprise huge dictionaries. Our top choice of translation programs are Power Translator, Systran Premium Translator and ABBYY Lingvo. These state of the art applications, as tested in comparison with other tools on the market, are able to produce a raw draft of nearly human quality, only requiring a light post-editing review. For full feature description please click here .
