Applications Machine Translation

While no system provides the holy grail of fully automatic high-quality machine translation of unrestricted text, many fully automated systems produce reasonable output. The quality of machine translation is substantially improved if the domain is restricted and controlled.

Despite their inherent limitations, MT programs are used around the world. Probably the largest institutional user is the European Commission. The MOLTO project, for example, coordinated by the University of Gothenburg, received more than 2.375 million euros project support from the EU to create a reliable translation tool that covers a majority of the EU languages. The further development of MT systems comes at a time when budget cuts in human translation may increase the EU’s dependency on reliable MT programs. The European Commission contributed 3.072 million euros (via its ISA programme) for the creation of MT@EC, a statistical machine translation program tailored to the administrative needs of the EU, to replace a previous rule-based machine translation system.

Google has claimed that promising results were obtained using a proprietary statistical machine translation engine. The statistical translation engine used in the Google language tools for Arabic <-> English and Chinese <-> English had an overall score of 0.4281 over the runner-up IBM’s BLEU-4 score of 0.3954 (Summer 2006) in tests conducted by the National Institute for Standards and Technology.

With the recent focus on terrorism, the military sources in the United States have been investing significant amounts of money in natural language engineering. In-Q-Tel (a venture capital fund, largely funded by the US Intelligence Community, to stimulate new technologies through private sector entrepreneurs) brought up companies like Language Weaver. Currently the military community is interested in translation and processing of languages like Arabic, Pashto, and Dari.[citation needed] Within these languages, the focus is on key phrases and quick communication between military members and civilians through the use of mobile phone apps. The Information Processing Technology Office in DARPA hosts programs like TIDES and Babylon translator. US Air Force has awarded a $1 million contract to develop a language translation technology.

The notable rise of social networking on the web in recent years has created yet another niche for the application of machine translation software – in utilities such as Facebook, or instant messaging clients such as Skype, GoogleTalk, MSN Messenger, etc. – allowing users speaking different languages to communicate with each other. Machine translation applications have also been released for most mobile devices, including mobile telephones, pocket PCs, PDAs, etc. Due to their portability, such instruments have come to be designated as mobile translation tools enabling mobile business networking between partners speaking different languages, or facilitating both foreign language learning and unaccompanied traveling to foreign countries without the need of the intermediation of a human translator.

Despite being labelled as an unworthy competitor to human translation in 1966 by the Automated Language Processing Advisory Committee put together by the United States government,  the quality of machine translation has now been improved to such levels that its application in online collaboration and in the medical field are being investigated. In the Ishida and Matsubara lab of Kyoto University, methods of improving the accuracy of machine translation as a support tool for inter-cultural collaboration in today’s globalized society are being studied. The application of this technology in medical settings where human translators are absent is another topic of research however difficulties arise due to the importance of accurate translations in medical diagnoses.