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<Paper uid="H89-2015">
  <Title>NEW POSSIBILITIES IN MACHINE TRANSLATION</Title>
  <Section position="3" start_page="0" end_page="99" type="intro">
    <SectionTitle>
INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> The possibility of using computers to perform the translation of documents among various languages was one of the earliest goals of Natural Language Processing and, indeed, one of the earliest of Artificial Intelligence. In the typical approach taken in the sixties, a parser program was equipped with a grammar and lexicon of the source language and a generator program with a grammar and lexicon of the target language, and the remainder consisted of a set of rules of correspondences among syntactic structures or lexical items. These approaches were soon proved naive by translations such as the now-famous &amp;quot;the vodka is strong but the meat is rotten&amp;quot; from &amp;quot;the spirit is willing but the flesh is weak&amp;quot;. It was apparent that semantic information had somehow to be taken seriously (at least to the point of knowing that, for example, &amp;quot;spirit&amp;quot; may indeed be &amp;quot;vodka&amp;quot;, but not when used as an active agent who can be &amp;quot;willing&amp;quot;). Since the early 60's, Machine Translation (MT) as a field of inquiry has largely lain dormant in the U.S., with the exception of a few large projects (such as at the University of Texas, Austin \[Bennett 82\]) and a few smaller projects (such as at Yale University \[Lytinen 84\]). In recent years, however, especially under the impetus of Japanese and European efforts at addressing the problem, U.S. interest in MT research has been on the increase.</Paragraph>
    <Paragraph position="1"> The principal reason for the increase is the ongoing development of tools and techniques that enable the performance of certain tasks with more thoroughness and success than was possible earlier (see,  for example, \[Carbonell et al. 81, Carbonell &amp; Tomita 87, Nirenburg 87, Arnold 86, Nakamura et al. 88, Laubsch et al. 84, Amano 86\]). There has been a steady growth of the capabilities of parsers and generators, the coverage of grammars, and the power and sophistication of knowledge representation techniques. In addition, two recent developments have the nature of breakthroughs that will greatly enhance future MT systems: the incorporation of disjunction in KL-ONE-Iike representation systems, and the development of general-purpose language-based taxonomic ontologies of representation.</Paragraph>
    <Paragraph position="2"> Overall, the field has grown wiser since the 60's: the newer MT projects are all less ambitious in scope than the early ones. Though nobody today would promise to deliver a system that performs perfect translation in even a relatively restricted domain, researchers feel comfortable about proposing systems that perform the first pass of a translation, producing a rough copy of the text in the target language, which would then be edited for stylistic smoothness and fluent cadence by a human editor. Such systems are called Machine-Aided Translation (MAT) systems. Since such systems significantly reduce the problems and costs of translation, they are in high demand in industry and industrial research throughout the world.</Paragraph>
    <Paragraph position="3"> For example, three MAT systems currently in use in Japan reputedly reduce the time of translation of technical documents by about 50%; two of them are commercially available for under $70,000 \[Time 89\].</Paragraph>
    <Paragraph position="4"> The following passage from the invitation to an international seminar on MT organized by IBM (held in Munich, West Germany, in August 1989) summarizes the point: There is a growing need for translation (estimated at 15-25 percent per annum) in commerce, science, governments, and international organizations. This is due to increased international cooperation and competition, an ever-growing volume of text to be communicated, often in multiple languages, world-wide electronic communication, and more emphasis in countries on the use of national language in documents and systems. The opening of the European market in 1992 will add significantly to these factors.</Paragraph>
    <Paragraph position="5"> At the same time, automated machine translation of natural language is reaching the stage where it can deliver significant cost savings in translation production, and vastly increase the scope of information retrieval, although fully automated high-quality translation is technically not feasible today and in the near future.</Paragraph>
    <Paragraph position="6"> \[H. Lehmann and P. Newman, IBM Scientific Centers in Heidelberg and Los Angeles, 1989.\] This paper presents a case for the establishment of a modest MAT program under Darpa support. After providing some background and describing new technological capabilities, it discusses a framework in which a few small MAT projects could be brought into existence for a modest investment and motivated toward achieving a high level of performance in five years.</Paragraph>
  </Section>
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