Communication in large distributed AI Systems for Natural Language Processing

Communication in large distributed AI Systems for Natural Language Processing Jan W. Amtrup* University o:f [Im:nburg, Com p. Sci. l)ept. Vogt-KSlln-Str. 30 11)-22527 I [amburg amtrul)~.in for:matilc u hi- hanlburg.de JSrg Benra* DFKI GmbH ]~rwm-Schrodinger-St;r. (Bau 57) ])-67663 Kaiserslautcrn t)enrag~d fki.uni-kl.de Abstract We. are going to describe the design and implementatior, of a connnuniea- lion system l.or large AI projects, ca- pable of supporting various software components in a heterogeneous hard- ware and programming-language envi- ronment. The system is based on a rood- ification of the channel approach intro- duced by Hoare (1978). It is a three- layered approach with a de facto stan- dard network layer (PVM), core rou- tines, and interfaces to live different pro- gramming languages together with SUl)- port l.or the transparent exchange of complex data types. A special compo- nent takes over: name service functiorrs. It also records the actual configuration of the modules present in the application and the created channels. We describe the integration of this com- munication facility in two versions of a speech-to-speech translation system, which ditfer with regard to quality and quantity of data. distributed within tire applications and with regard to the de- gree of interactivity involved in process- ing. 1 Introduction (hu:rently, there is a trend of lmilding large AI- systems in a distrilulted, agent-oriented manner. '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 accept- ably last. If pure speed is not the primary moti- vation, the incorporation of several modules, each *'l'his rescm'ch was funded by the Federal Min- istry of l~;dncat;ion, Science., ll.esem'ch and Technol- ogy (IIMBF) in the framework of the VI,;HIIMOBIL Project raider Granl, s 01 IV 10l A/O and 01 IV 101 G. of them possibly being realized in a different pro- gramming language or even a different program- ruing lmradignl, demands complex interfaces be- tween these modules, l,'urthermore, only modular- ization makes it possible to develop applications in a truly distributed inanner without the need to eol)y and install versions repeatedly over. ~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 in- terface 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 proto- cols between components which is natural to a certain degree, due to the different tasks per- formed by the components and the purpose of the internee data but; also to a number of ditf~rent implementation strategies :['or interfaces. In this pal)er , we present ICE, the Intarc Communication Environment (Amtrup, 1995), an implementation of a channel-oriented, multi- architecture, multi-language communication mod- ule for large, A l-systems, which is particularly use- ful for systems integrating speech and language processing. A channel-oriented model ['or interaction re- lations between …

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