Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-26T08:42:24.707Z Has data issue: false hasContentIssue false

Several knowledge models and a blackboard memory for human-machine robust dialogues

Published online by Cambridge University Press:  12 September 2008

Violaine Prince
Affiliation:
LIMSI - CNRS, PO Box 133, 91403 Orsay cedex, France. e-mail: prince@limsi.fr
Didier Pernel
Affiliation:
THOMSON-CSF, LCR: Domaine de Corbeville, 91404 Orsay cedexFrance. e-mail: pernel@thomson-lcr.fr

Abstract

This contribution focuses on a dialogue model using an intelligent working memory that aims at facilitating a robust human-machine dialogue in written natural language. The model has been designed as the core of an information seeking dialogue application. The particularity of this project is to rely on the potent interpretation and behaviour capabilities of pragmatic knowledge. Within this framework, the designed dialogue model appears as a kind of ‘forum’ for various facets, impersonated by different models extracted from both intentional and structural approaches of conversation. The approach is based on assuming that multiple expertise is the key to flexibility and robustness. Also, an intelligent memory that keeps track of all events and links them together from as many angles as necessary is crucial for multiple expertise management. This idea is developed by presenting an intelligent dialogue history which is able to complement the wide coverage of the co-operating models. It is no longer a simple chronological record, but a communication area, common to all processes. We illustrate our topic through examples brought out from collected corpora.

Type
Articles
Copyright
Copyright © Cambridge University Press 1995

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Allen, J., and Perrault, R., 1980. Analyzing intention in utterances. Artficial Intelligence 15: 143–78.Google Scholar
Allwood, J., 1976. Linguistic communication as action and cooperation. Gothenburg University Monographs Linguistics, 1. Goteborg, Sweden.Google Scholar
Austin, J., 1962. How to Do Things with Words. Oxford University Press.Google Scholar
Bilange, E., 1991. Moderation du dialogue oral finalise personne-machine par une approche structurelle. PhD Thesis. Rennes University.Google Scholar
Black, B., (ed.) 1991. Functional Design (PLUS Delivrable No. 2.1). ESPRIT P5424.Google Scholar
Bunt, H., 1985. Mass Terms and Model-theoretic Semantics. Cambridge University Press.Google Scholar
Bunt, H., 1989. Information dialogues as communicative action in relation to partner modelling and information processing. In F.N., and Taylor, D.G., (eds.), The Structure of Multimodal Dialogue. North Holland.Google Scholar
Carberry, S., 1988. Modelling the user's plans and goals. Computational Linguistics. 14: 2337.Google Scholar
Cohen, P., Morgan, J., and Pollack, M., 1990. Intentions in Communication. Bradford Books at MIT Press.Google Scholar
Grau, B., Sabah, G., and Vilnat, A., 1993. A pragmatic driven human-machine dialogue system. Think 2. University of Tilburg.Google Scholar
Grice, P., 1975. Logic and conversation. In Coles, and Morgan, , (eds.), Syntax and Semantics. Academic Press. Pp. 4158.Google Scholar
Grosz, B., and Kraus, S., 1993. Collaborative plans for group activities. In Proceedings of the 13th International Joint Conference on Artificial Intelligence.Chambery, France. Pp. 367–73.Google Scholar
Grosz, B., and Sidner, C., 1986. Attention, intentions and the structures of discourse. American Journal of Computational Linguistics 12(3): 175204.Google Scholar
Grosz, B., and Sidner, C., 1990. Plans for discourse. In Cohen, P., Morgan, J., and Pollack, M., (eds.), Intentions in Communication. Bradford Books at MIT Press.Google Scholar
Hovy, E., 1993. Automated discourse generation using discourse structure relations. Artificial Intelligence 63: 341–85.CrossRefGoogle Scholar
Kobsa, A., 1989. A taxonomy of beliefs and goals for user models in dialog systems. In Kobsa, A.Kobsa, A. and Wahlster, W., (eds.) 1989. User Models in Dialog Systems. Springer-Verlag.Google Scholar
Levine, J.M., 1990. Pragma – a flexible bidirectional dialogue system. In Proceedings of the 8th National Conference onf Artificial Intelligence, AAAI.Boston, MA. Pp 964–9.Google Scholar
Luzzati, D., 1989. Recherches sur le dialogue homme-machine: modeles linguistiques et traitements automatiques. Doctorat d'état ès lettres, Paris III.Google Scholar
Mann, W.C., and Thompson, S.A., 1986. Rhetorical Structure Theory: description and construction of text structures. In Kempen, G. (ed.), Natural language Generation: New Results in Artificial Intelligence, Psychology, Linguistics. Kluwer. pp. 279300Google Scholar
McCoy, K., and Cheng, J., 1990. Focus of attention: Constraining what can be said next. In Swartout, M., (ed.), Natural Language Generation in Artificial Intelligence and Computational Linguistics. Kluwer.Google Scholar
Moeschler, J., 1985. Argumentation et conversation, éléments pour une analyse pragmatique du discours. Paris: Hatier.Google Scholar
Moeschler, J., 1989. Modélisation du dialogue. Représentation de l'inférence argumentaire. Paris: Hermés.Google Scholar
Morik, K., 1988. Discourse models, dialog memories and user models. Computational Linguistics 14(3): 8597.Google Scholar
Nivre, J., (ed.) 1992. PLUS Corpora Analysis (PLUS Deliverable No 1.3). ESPRIT P5424.Google Scholar
Pernel, D. 1991a. Analyse du Corpus de “PLUS” (Internal Document) LIMSI.Google Scholar
Pernel, D. 1991b. Le Corpus “PLUS” (Internal Document) LIMSI.Google Scholar
Pernel, D., 1994. Gestion des buts multiples de l'utilisateur dans un dialogue Homme-machine de recherche d'information. PhD Dissertation, University of Paris XI.Google Scholar
Perrault, R. 1991. Representing user's beliefs in a modal framework. In 1st PLUS Pragmatics Summer Workshop. Sorrento, Italy.Google Scholar
Pierrel, J.-M., 1987. Dialogue oral homme-machine. Hermés.Google Scholar
Pollack, M., 1990. Plans as complex mental attitudes. In Cohen, P., Morgan, J. and Pollack, M. (eds), In tentions in Communication. Bradford Books at MIT Press.Google Scholar
Pollard, C., and Sag, L.A., 1987. Information-based syntax and semantics. Vol 1, ‘Fundamentals’ CSLI Lecture Notes 13. Standford University.Google Scholar
Prince, V., and Pernel, D., 1992. Un modele federateur pour le dialogue Homme-machine robuste en langage naturel écrit: le modèle de l'enonciation du projet ESPRIT II/PLUS. In Proceedings of the ‘DIALOGUE Workshop of the Man-machine Communication Pole of Research’. Dourdan, France. Pp. 131147.Google Scholar
Prince, V., and Pernel, D., 1994. Querying Yellow Pages in natural language: a corpus based modelling. In Proceedings of the 3rd International Conference on Cognitive Science in Natural Language Processing (CSNLP-94).Dublin, Ireland. Pp. 114121.Google Scholar
Prince, V., Pernel, D., and Godin, C., 1991. Discourse Model & Dialogue History (Internal PLUS Paper). ESPRIT P5424.Google Scholar
Roulet, E., Auchlin, A., Moeschler, J., Rubattel, C., and Schelling, M., 1985. L'articulation du discours en français contemporain. Peter Lang.Google Scholar
Sabah, G., 1991a. Control in the PLUS architecture (Internal PLUS paper). ESPRIT P5424.Google Scholar
Sabah, G., 1991b. Dialogue homme-machine: pragmatique et robustesse. In Proceedings of RF-1A 91, Villeurbanne: AFCET.Google Scholar
Sabah, G., Godin, C., and Derain, A., 1991. ‘Proposition for the control architecture of PLUS’ (Internal PLUS Paper in ‘Deliverable 1.2: FUNCTIONAL DESIGN’ (Bill Black ed.)). ESPRIT P5424.Google Scholar
Sabah, G., and Briffault, X., 1993 CARAMEL: A step towards reflection in natural language understanding systems. In Proceedings of IEEE TAI-93, Boston, MA.Google Scholar
Schlegoff, E.A., and Sacks, H., 1973. Opening up closings. Semiotica 7(4): 289327.Google Scholar
Searle, J., 1969. Speech Acts. Cambridge University Press.Google Scholar
Sperber, D., and Wilson, D., 1986. Relevance: Communication and Cognition. Basil Blackwell.Google Scholar
Taylor, M., 1988. Layered protocols for computer-human dialogue: I: Principles. International Journal of Human-Machine Studies 28: 175218.Google Scholar
Van Beek, P., and Cohen, R., 1991. Resolving the plan ambiguity for cooperative response generation. In Proceedings of the 12th International Joint Conference on Artificial Intelligence.Sydney, Australia. Pp. 938–44.Google Scholar
Vilnat, A., 1984. L'elaboration d'interventions pertinentes dans une conversation hommemachine. PhD Dissertation. Université Pierre et Marie Curie (Paris VI).Google Scholar
Vilnat, A., 1989. Relevant responses in man-machine conversation. In Taylor, Neél, and Bouwhuis, , (eds.), The Structure of Multimodal Dialogue. North-Holland. Pp. 399406Google Scholar
Vilnat, A., and Nicaud, L., 1992. Le Projet STANDIA. In Proceedings of the ‘DIALOGUE Workshop of the Man-machine Communication Pole of Research’.Dourdan, France.Google Scholar
Vilnat, A., and Sabah, G., 1985. La gestion du dialogue dans un système de questions-réponses. In Proceedings of Congres AFCET 5ème génération.Paris.Google Scholar
Wachtel, T., 1988. Making sense of corrupt input: conceptual interpretation in LOK.I. In Proceedings of the IEE colloquium of NLP. Digest 1988–118.Google Scholar
Wahlster, W. and Kobsa, A. 1986. Dialogue-based user models. Proceedings of IEEE 74(7): 948–60.Google Scholar