By John Newton
Translators, approach designers, process operators and researchers current a finished advisor to laptop translation: its historical past, its successes, its barriers and its capability.
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Extra info for Computers in Translation: A Practical Appraisal
Furthermore, the central role of Japan in recent technological advances makes the need for speedy access to translated Japanese documentation crucial. Finally, machine translation has emerged as an important test-bed for the larger fields of computational linguistics, NLP and AI in which the US has sustained a high level of research activity. From this point of view, therefore, MT is not only an end in itself but an important means to other objectives. The apparent revival of interest in MT in the USA within government, the private sector, the academic community and even the Amerian public appears to stem from a mixture of motives ranging from economic necessity through technolog ical chauvinism to scientific aspiration.
The Commission of the European Communities, after initial abortive attempts to expand the imported American SYSTRAN system to meet its multilingual needs, decided to start its own R&D programme in MT. This decision proved revitalizing for European MT and led to the expansion and consolidation of existing MT research centres and to the establishment of new centres in other countries, many of which had no previous experience in the field. While MT in Europe cannot be uniquely identified with EUROTRA (see below), its contribution to the emergence of an integrated MT community with an established communications infrastructure—which contrasts sharply with the fragmentation of expertise and resources in the United States— should not be ignored.
Maas, D. (1987) ‘The Saarbrücken automatic translation system (SUSY)’, in Overcoming the language barrier, Commission of the European Communities, Munich: Verlag Dokumentation, vol. 1:585–92. , Tsujii, J. and Nakamura, J. (1985) ‘The Japanese government project for machine translation’, Computational Linguistics 11:91–110. Nirenburg, S. (1989) ‘Knowledge-based machine translation’, Machine Translation, 4:5–24. , Sadler, V. M. (eds) (1986) Word Expert Semantics: an Interlingual Knowledge-based Approach, (Distributed Language Translation 1), Dordrecht: Foris.