Robust Interaction through Partial Interpretation and Dialogue Management

Robust Interaction through Partial Interpretation and Dialogue Management Arne JSnsson and Lena StrSmb~ick* Department of Computer and Information Science LinkSping University, S - 58183 LinkSping, Sweden email: arj@ida.liu.se lestr@ida.liu.se Abstract In this paper we present results on developing ro- bust natural language interfaces by combining shal- low and partial interpretation with dialogue manage- ment. The key issue is to reduce the effort needed to adapt the knowledge sources for parsing and in- terpretation to a necessary minimum. In the paper we identify different types of information and present corresponding computational models. The approach utilizes an automatically generated lexicon which is updated with information from a corpus of simulat- ed dialogues. The grammar is developed manually from the same knowledge sources. We also present results from evaluations that support the approach. 1 Introduction Relying on a traditional deep and complete analysis of the utterances in a natural lan- guage interface requires much effort on building grammars and lexicons for each domain. An- alyzing a whole utterance also gives problems with robustness, since the grammars need to cope with all possible variations of an utter- ance. In this paper we present results on devel- oping knowledge-based natural language inter- faces for information retrieval applications uti- lizing shallow and partial interpretation. Simi- lar approaches are proposed in, for instance, the work on flexible parsing (Carbonell and Hayes, 1987) and in speech systems (cf. (SjSlander and Gustafson, 1997; Bennacef et al., 1994)). The interpretation is driven by the information needed by the background system and guided by expectations from a dialogue manager. The analysis is done by parsing as small parts of the utterance as possible. The infor- mation needed by the interpretation module, i.e. grammar and lexicon, is derived from the database of the background system and infor- mation from dialogues collected in Wizard of * Authors are in alphabetical order Oz-experiments. We will present what types of information that are needed for the interpreta- tion modules. We will also report on the sizes of the grammars and lexicon and results from applying the approach to information retrieval systems. 2 Dialogue management Partial interpretation is particularly well-suited for dialogue systems, as we can utilize informa- tion from a dialogue manager on what is ex- pected and use this to guide the analysis. Fur- thermore, dialogue management allows for focus tracking as well as clarification subdialogues to further improve the interaction (JSnsson, 1997). In information retrieval systems a common user initiative is a request for domain concept information from the database; users specify a database object, or a set of objects, and ask for the value of a property of that object or set of objects. In the dialogue model this can be modeled in two focal parameters: Objects relat- ed to database objects and Properties modeling the domain concept information. The Proper- ties parameter models the domain concept in a sub-parameter termed Aspect which can be specified in another sub-parameter termed Val- ue. The specification of these parameters in turn depends on information …

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