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<Paper uid="C96-1008">
  <Title>Communication in large distributed AI Systems for Natural Language Processing</Title>
  <Section position="2" start_page="0" end_page="35" type="intro">
    <SectionTitle>
1 Introduction
</SectionTitle>
    <Paragraph position="0"> (hu:rently, there is a trend of lmilding large AIsystems in a distrilulted, agent-oriented manner.</Paragraph>
    <Paragraph position="1"> 'l'he complex tasks performed e.g. by systems with nmltimodal user interfaces or by systems tackling the processing of spontaneous speech often require more than one computer in order to run acceptably last. If pure speed is not the primary motivation, the incorporation of several modules, each *'l'his rescm'ch was funded by the Federal Ministry of l~;dncat;ion, Science., ll.esem'ch and Technology (IIMBF) in the framework of the VI,;HIIMOBIL Project raider Granl, s 01 IV 10l A/O and 01 IV 101 G.</Paragraph>
    <Paragraph position="2"> of them possibly being realized in a different programming language or even a different programruing lmradignl, demands complex interfaces between these modules, l,'urthermore, only modularization makes it possible to develop applications in a truly distributed inanner without the need to eol)y and install versions repeatedly over.</Paragraph>
    <Paragraph position="3"> ~l'he actual realization of tire interfaces should ground on a sound theoretical framework, and it; shoukl be as independent as possible from the module implementations. TypicMly, when an interface between two subcomponents of a system is needed, at \[irst very simple means e.g. file interfaces or simple pipes are considered. This does uot only lead to a variety of different protocols between components which is natural to a certain degree, due to the different tasks performed by the components and the purpose of the internee data but; also to a number of ditf~rent implementation strategies :\['or interfaces.</Paragraph>
    <Paragraph position="4"> In this pal)er , we present ICE, the Intarc Communication Environment (Amtrup, 1995), an implementation of a channel-oriented, multiarchitecture, multi-language communication module for large, A l-systems, which is particularly useful for systems integrating speech and language processing.</Paragraph>
    <Paragraph position="5"> A channel-oriented model \['or interaction relations between software modules seemed to be the most suitable system for our needs. We adopted the CSP-approach (Horn:e, 11978) and its actual realization in the transputer hardware ((~rahatn and King, 1990). This core flmctional model was slightly modified to satisfy the needs emerging from ext)eriences with actual systems.</Paragraph>
    <Paragraph position="6"> We decided not to implement all communication flmctions from scratch, \[)tit instead we use PVM, the Parallel Virtual Machine (Geist et al., 1994), a widespread process-comnmnication software, which turned out to be extremely reliable.</Paragraph>
    <Paragraph position="7"> We will desribe how the communication system has been integrated within Verbmobil, a large research project tbr automatic speech-to-speech translation (Wahlster, 1993). ICE is used for the w~rious I)rototypes of the interpretation system.</Paragraph>
    <Paragraph position="8">  We describe experiences and results of the work on the first demonstrator. Furthermore, we show that ICE is flexible enough to be used in architectural experiments and we are going to report some of the experiences made with them.</Paragraph>
  </Section>
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