Robust Parsing of Spoken Dialogue Using Contextual Knowledge and Recognition Probabilities

In this paper we describe the linguistic processor of a spoken dialogue system. The parser receives a word graph from the recognition module as its input. Its task is to find the best path through the graph. If no complete solution can be found, a robust mechanism for selecting multiple partial results is applied. We show how the information content rate of the results can be improved if the selection is based on an integrated quality score combining word recognition scores and context-dependent semantic predictions. Results of parsing word graphs with and without predictions are reported.Comment: 4 pages, LaTex source, 3 PostScript figures, uses epsf.sty and ETRW.sty, to appear in Proceedings of ESCA Workshop on Spoken Dialogue Systems, Denmark, May 30-June

Combining Expression and Content in Domains for Dialog Managers

We present work in progress on abstracting dialog managers from their domain in order to implement a dialog manager development tool which takes (among other data) a domain description as input and delivers a new dialog manager for the described domain as output. Thereby we will focus on two topics; firstly, the construction of domain descriptions with description logics and secondly, the interpretation of utterances in a given domain.Comment: 5 pages, uses conference.st

Modelling Users, Intentions, and Structure in Spoken Dialog

We outline how utterances in dialogs can be interpreted using a partial first order logic. We exploit the capability of this logic to talk about the truth status of formulae to define a notion of coherence between utterances and explain how this coherence relation can serve for the construction of AND/OR trees that represent the segmentation of the dialog. In a BDI model we formalize basic assumptions about dialog and cooperative behaviour of participants. These assumptions provide a basis for inferring speech acts from coherence relations between utterances and attitudes of dialog participants. Speech acts prove to be useful for determining dialog segments defined on the notion of completing expectations of dialog participants. Finally, we sketch how explicit segmentation signalled by cue phrases and performatives is covered by our dialog model.Comment: 17 page

Adaptation of NLP Techniques to Cultural Heritage Research and Documentation

The WissKI system provides a framework for ontology based science communication and cultural heritage documentation. In many cases, the documentation consists of semi-structured data records with free text fields. Most references in the texts comprise of person and place names, as well as time specifications. We present the WissKI tools for semantic annotation using controlled vocabularies and formal ontologies derived from CIDOC Conceptual Reference Model (CRM). Current research deals with the annotations as building blocks for event recognition. Finally, we outline how the CRM helps to build bridges between documentation in different scientific disciplines