A Robust and Efficient Three-Layered Dialogue Component for a Speech-to-Speech Translation System

A Robust and Efficient Three-Layered Dialogue Component for a Speech-to-Speech Translation System* Jan Alexandersson and Elisabeth Maier and Norbert Reithinger DFKI GmbH, Stuhlsatzenhausweg 3, D-66123 Saarbrficken, Germany {alexanders son, maier, reithinger}~dfki, uni- sb. de Abstract We present the dialogue component of the speech-to-speech translation system VERBMOBIL. In contrast to conventional dialogue systems it mediates the dia- logue while processing maximally 50% of the dialogue in depth. Special require- ments (robustness and efficiency) lead to a 3-layered hybrid architecture for the dialogue module, using statistics, an automaton and a planner. A dialogue memory is constructed incrementally. 1 Introduction VERBMOBIL combines the two key technologies speech processing and machine translation. The long-term goal of this project is the development of a prototype for the translation of spoken di- alogues between two persons who want to find a date for a business meeting (for more detail on the objectives of VERBMOBIL see (Wahlster, 1993)). A special characteristic of VERBMOBIL is that both participants are assumed to have at least a pas- sive knowledge of English which is used as inter- mediate language. Translations are produced on demand so that only parts of the dialogue are pro- cessed. If VERBMOBIL is inactive, shallow process- ing by a keyword spotter takes place which allows the system to follow the dialogue at least partially. In this paper focus is on the description of the dialogue component, which processes the interac- tion of the two dialogue partners and builds a rep- resentation of the discourse. Dialogue processing in VERBMOBIL differs from systems,like SUNDIAL (Andry, 1992) in two important points: (1) VERB- MOBIL mediates the dialogue between two human dialogue participants; the system is not a partic- ipant of its own, i.e. it does not control the di- alogue as it happens in the flight scheduling sce- nario of SUNDIAL; (2) VERBMOBIL processes maxi- mally 50% of the dialogue contributions in depth, *The research within VERBMOBIL presented here is funded by the German Ministry of Research and Tech- nology under grant 011V101K/1. i.e. when the 'owner' of VERBMOBIL speaks Ger- man only. The rest of the dialogue can only be followed by a keyword spotter. In the remainder of this paper first the require- ments of the VERBMOBIL setting with respect to functionality and design of the dialogue compo- nent section are introduced. Then a hybrid archi- tecture for the dialogue component and its embed- ding into the VERBMOBIL prototype are discussed. Finally, results from our implemented system are presented. We conclude with an outline of future extensions. 2 Tasks of the Dialogue Component The dialogue component within VERBMOBIL has four mQor tasks: (1) to support speech recognition and linguis- tic analysis when processing the speech signal. Top-down predictions can be made to restrict the search space of other analysis components to get better results in shorter time (Young et al., 1989; Andry, 1992)). For instance, predictions about a speech act can be used to narrow down the set of words which are likely to occur in the …

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