An Efficient Kernel for Multilingual Generation in Speech-to-Speech Dialogue Translation

An Efficient Kernel for Multilingual Generation in Speech-to-Speech Dialogue Translation Tilman Becker and Wolfgang Finkler and Anne Kilger and Peter Poller German Research Center for Artificial Intelligence (DFKI GmbH) Stuhlsatzenhausweg 3 D 66123 Saarbriicken Germany becker0dfki.de, fink]_er0dfki.de, kilger~dfki.de, pol]_er@dfki.de Abstract We present core aspects of a fully implemented generation component in a multilingual speech- to-speech dialogue translation system. Its de- sign was particularly influenced by the neces- sity of real-time processing and usability for multiple languages and domains. We devel- oped a general kernel system comprising a mi- croplanning and a syntactic realizer module. The microplanner performs lexical and syntac- tic choice, based on constraint-satisfaction tech- niques. The syntactic realizer processes HPSG grammars reflecting the latest; developments of the underlying linguistic theory, utilizing their pre-processing into the TAG formalism. The declarative nature of the knowledge bases, i.e., the microplanning constraints and the HPSG grammars allowed an easy adaption to new do- mains and languages. The successflfl integra- tion of our component into the translation sys- tem Verbmobil proved the fulfillment of the spe- cific real-time constraints. 1 Introduction In this paper we present core aspects of the mul- tilingual natural language generation compo- nent VM-GECO 1 that has been integrated into the research prototype of Verbmobil (Wahlster, 1993; Bub et al., 1997), a system for sponta- neous speech-to-speech dialog translation. In order to achieve multilinguality as ele- gantly as possible we found that a clear modu- lar separation between a language-independent general kernel generator and language-specific parts which consist of syntactic and lexical knowledge sources was a very promising ap- proach. Accordingly, our generation component 1VM-GECO is an acronym for "VerbMobil GEnera- tion COmponents." consists of one kernel generator and language- specific knowledge sources for the languages used in Verbmobil: German and English with current work on Japanese. Additionally, the kernel generator itself can be modularized furthermore into two separate components. The task of the so called rni- croplarming component is to plan an utterance oil a phrase- or sentence-level (Hovy, 1996) in- cluding word--choice (section 2). It generates an annotated dependency structure which is used by the syntactic generation component to re- alize an appropriate surface string for it (sec- tion 3). Tile main goal of this further modular- ization is a stepwise constraining of the search- space of alternative linguistic realizations, using abstracted views on different choice criteria. Multilingual generation in dialog translation imposes strong requirements on the generation module. A very prominent problem is the non- welltbrmedness (incorrectness, irrelevance, and inconsistency) of spontaneous input. It fbrces the realization of robust generation to be able to cope with erroneous and incomplete input data so that the quality of the generated out- put may vary between syntactically correct sen- tences and semanticMly understandable utter- ances. On the level of knowledge sources this is achieved by using a highly declarative HPSG grammar which very closely reflects the latest developments of the underlying linguistic the- ory (Pollard and Sag, 1994) and covers phe- nomena of spoken language. This HPSG is compiled …

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