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<Paper uid="H91-1006">
  <Title>MACHINE TRANSLATION IN EUROPE</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> Whereas in the United States work in machine translation (MT) has only recently been reinstated as a 'respectable' natural language processing (NLP) application, it has long been considered a worthwhile and interesting topic for research and development in both Europe and Japan. In terms of number of projects in one sub-field of computational linguistics, MT is currently perhaps the most important application. 1 One obvious reason for this is simply the daily awareness that people communicate in languages other than English, a situation that naturally encourages an interest in translation.</Paragraph>
    <Paragraph position="1"> On a practical level, for example, every television cable system in Europe broadcasts stations from numerous countries, and on the political level, the European Community (EC) is committed to protecting the language of each of the Member States, which implies providing numerous translation services.</Paragraph>
    <Paragraph position="2"> From an economic viewpoint, every company knows that in order to market its products, the documentation must be in the language of the target country. And a last motivation for interest in MT, which was also the origin of MT activities in the US and an important concern for Japan, is the desire for better access to information--important documents often exist in some foreign language.</Paragraph>
    <Paragraph position="3"> Yet MT in Europe is not viewed as just a matter of developing working MT systems for commercial and practical needs--it is also accepted as a legitimate topic of research. The view of MT as a test bed for NLP work has long been defended in the United States (Kay,1980). Reasons why this position has only recently gained favor can be attributed to Bar-Hillel's strong view on the impossibility of high-quality MT coupled with the far-reaching effects the ALPAC report (1966) had on funding in the US. All direct funding for translation was withdrawn and redirected to more basic research and thus linguistics and AI work prospered. Though practical work continued, as well as a real need for translation, 2 MT fell into disrepute as an academically respectable enterprise. While there is consensus that fully automatic high quality MT of unrestricted text is impossible, it is nevertheless an attractive long-term goal, similar to pursuits in artificial intelligence. In Europe, a growing number of researchers in computational linguistics regard translation as a challenging field of application. Eased on developments in the field such as a more rigorous formalization of semantics (e.g., Montague At the two most recent Coling conferences, for example, the number of papers devoted to issues in MT constituted the largest single topic; and this figure does not take into account all the general NLP papers presented by the MT projects.</Paragraph>
    <Paragraph position="4"> Ironically, the Georgetown system, on which the ALPAC report was based, continued to be used in Europe, until well into the 70s and Systran, a direct descendant, is still the most widely used commercial MT system.</Paragraph>
    <Paragraph position="5"> grammar), the attention paid to formal and computational properties of linguistic theories (e.g., LFG and GPSG) and the definition and implementation of linguistically problem-oriented computational methods (e.g., unification), it is quite natural that attempts are being made to test their adequacy with regard to problems of translation.</Paragraph>
    <Paragraph position="6"> The multilingual setting of Europe, where translation is a fact of life, along with its varied and decentralized funding agencies (including EC, national and regional programs), as opposed to the more centralized nature of US federal agencies, helps explain why the ALPAC report had less of an impact overseas. Machine translation has a long and relatively stable tradition in Europe. Similar to the early work with computers and language in the United States where CL and MT were synonymous, MT projects in Europe have served as a vehicle for developing expertise in computational linguistics in centers which had little experience in the field. This latter point is particularly true in the Eurotra project; Greece, for example, had no tradition in computational linguistics.</Paragraph>
    <Paragraph position="7"> The historical and socio-political references have been introduced as background material, given the rather strong positions taken up by members in and out of the community over the last decades. The distinction between research and development or theoretical vs. practical, though somewhat artificial (and definitely a touchy issue in the community), serves as a means of clarifying and motivating what people are working on and why. The extreme view repeatedly put forward by M. Kay that &amp;quot;all machine translation of natural languages is experimental ...&amp;quot; (Kay, 1984:75) is, in my view, correct. There are nevertheless things that we can accomplish, albeit imperfectly, and from which we can learn both about language and about translafion--a situation similar to all NLP work. My purpose here is to distinguish major topics currently popular in MT work and to identify the projects and centers active in the field.</Paragraph>
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