Abstract
We describe a problem solving framework for a knowledge based approach to signal understanding. The risk of erroneous analysis makes advisable the use of well-experimented probabilistic control methods. Such methods have been used in the past in task-specific applications, such as speech. Here they are generalized to the case of a deduction system, thus becoming applicable to a wider class of problems still maintaining their effectiveness. That results in a blackboard based framework where every knowledge source is abstracted as a set of operators, that allow integration of different deductive processes independently evolved, either forward or backward. Such framework allows the use of admissible control strategies proposed in the literature.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
P.Bosco, E.Giachin, G.Giandonato, G.Martinengo, C.Rullent, 1987. “A Parallel Architecture for Signal Understanding through Inference on Uncertain Data’, Proc. Parallel Architectures and Languages Europe, Eindhoven, NL.
A.Brietzmann, U.Ehrlich, 1986. “The Role of Semantic Processing in an Automatic Speech Understanding System”, Proc. 11th Int. Conference on Computational Linguistics, Bonn, WG, pp. 596–598.
D.D.Corkill, V.R.Lesser, E.Hudlicka, 1982. “Unifying data-directed and goal-directed control: an example and experiments”, Proc. 2nd National Conf. on Artificial Intelligence (AAAI ‘82), Pittsburgh, PA, pp. 143–147.
L.D.Erman, F.Hayes-Roth, V.R.Lesser, D.Raj Reddy, 1980. “The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty”, ACM Computing Survey 12, pp. 213–253.
F.Hayes-Roth, V.R.Lesser, 1977. “Focus of Attention in the Hearsay-II Speech Understanding System”, Proc. 5th Int. Joint Conf. on Artificial Intelligence, Cambridge, Mass., pp. 27–35.
P.J.Hayes, A.G.Hauptmann, J.G.Carbonell, M.Tomita, 1986. “Parsing Spoken Language: a Semantic Caseframe Approach”, Proc. 11th Int. Conference on Computational Linguistics, Bonn, WG, pp. 587–592.
P.Laface, G.Micca, R.Pieraccini, 1987. “Experimental results on a large lexicon access task”, Proc. ICASSP-87, Dallas, Texas.
H.Penny Nii, 1986. “Blackboard Systems”. Part one: “Blackboard Application Systems, Blackboard Systems from a Knowledge Engineering Perspective”, The AI Magazine, August, 1986, pp.82–106. Part two: “The Blackboard Model of Problem Solving and the Evolution of Blackboard Architectures”, The AI Magazine, Summer, 1986, pp. 38–53.
A.Terry, 1983. “The Chrysalis Project: Hierarchical Control of Production Systems”, Tech. Rep. HPP-83–19, Stanford University, Heuristic Programming Project.
J.J.Wolf, W.A.Woods, 1980. “The HWIM Speech Understanding System”, in W.Lea (Ed.), Trends in Speech Recognition, Prentice-Hall, Engelwood Cliffs, N.J.
W.A.Woods, 1982. “Optimal Search Strategies for Speech Understanding Control”, Artificial Intelligence 18, pp. 295–326.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1987 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gemello, R., Giachin, E., Rullent, C. (1987). A Knowledge-Based Framework for Effective Probabilistic Control Strategies in Signal Understanding. In: Morik, K. (eds) GWAI-87 11th German Workshop on Artifical Intelligence. Informatik-Fachberichte, vol 152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-73005-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-73005-4_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-18388-4
Online ISBN: 978-3-642-73005-4
eBook Packages: Springer Book Archive