In the News

Jan Krikke After 50 years of research and tinkering, machine translation might be ready to compete with human translators. Several companies have announced breakthroughs or substantial progress in MT research in recent months. In January, for example, Steven Klein, CEO of New York-based Meaningful Machines, announced that his company successfully tested new translation algorithms that he says could lead to translation engines replacing human translators. "While our current prototype is already outperforming other systems on limited resources," says Klein, "we expect to see significant improvement to our quality as both the target language corpus and the dictionary continue to increase in size, with a realistic goal of reaching human quality." "Although the prototype is only partially complete," says Klein, "we recently began blind testing from Spanish to English, and our system is already performing at higher quality levels on the BLEU (Bilingual Evaluation Understudy) scale than any system we are aware of--0.6092. Systran, whose Spanish-to-English system is one of the best, scored a 0.5494 when we ran it through the same test, and the Systran system has been through many decades of development and incremental improvements." Meaningful Machines' test has not been independently verified, and the goal of reaching near-human quality translation will probably depend on some degree of pre- and post-editing for years to come. But, the growing number of global corporations (such as Philips, Samsung, and HP) and international agencies and institutions (such as the UN and the European Commission) using the technology illustrates that machine translation--the first nonnumerical application of AI--is finally delivering practical solutions. Popular perception of MT has suffered from low-quality "gisting" translation that Web-based translation engines, such as Babelfish and other online services, generate. But MT engines designed for limited domains, and tailor-made systems that use controlled language, are already delivering services. The site makes available a wealth of information previously inaccessible to non-Japanese speakers. MT has also made it to the desktop. The system is self-learning--it improves over time as its associative memory grows.