Review article
Ideological Purity Machine Translation's Pride or Pitfall? Frank Van Eynde, ed. Linguistic Issues in Machine Translation
London and New York: Pinter Publishers, 1993. viii + 239 pp. ISBN 1-85567-024-0 (Communication in Artificial Intelligence Series).

John Laffling
University of Wolverhampton
Table of contents

It can be maintained that all machine translation (MT) systems, whether of the research prototype or operational variety, are based on some (explicit or implicit) "theory", if 'theory' can be glossed simply as "a set of (system typespecific) principles". So, the early 'direct' systems, for example, were founded on the linguistically naive assumption that machine translation was basically a lexical task. SYSTRAN, which, being generally credited with a 65% accuracy rate, depending on the precise nature of the text, is still the system to beat, has continued in this vein, packing as much information as possible into its dictionaries. By the same token, research on knowledge-based MT at Carnegie- Mellon University in the United States can be said to be based on the "theory" that translation depends on two relations: one from source text to a meaning representation containing all translationally relevant information, the other from this meaning representation to the target text; and the contention that underlies the approach adopted by researchers at the IBM Laboratories at [ p. 82 ]Yorktown Heights is that for any text expressed in one language there is a text in another language, which is its translation, such that the relation between the two texts can be computed statistically from their surface form, by reference to transition probabilities.

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