An approach to computer speech recognition by direct analysis of the speech wave
An approach to computer speech recognition by direct analysis of the speech wave
Aspects of speech recognition by computer
Aspects of speech recognition by computer
An environment and system for machine understanding of connected speech.
An environment and system for machine understanding of connected speech.
The hearsay speech understanding system: an example of the recognition process
IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
IJCAI'73 Proceedings of the 3rd international joint conference on Artificial intelligence
IAAI '90 Proceedings of the The Second Conference on Innovative Applications of Artificial Intelligence
Representation and use of knowledge in vision
ACM SIGART Bulletin
IEEE Transactions on Computers
The Hearsay-I Speech Understanding System: An Example of the Recognition Process
IEEE Transactions on Computers
Artificial Intelligence: Cooperative Computation and Man-Machine Symbiosis
IEEE Transactions on Computers
Distributed Interpretation: A Model and Experiment
IEEE Transactions on Computers
Panel on dealing with uncertainty
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 2
Parallelism in artificial intelligence problem solving: a case study of hearsay II
IEEE Transactions on Computers - Special issue on parallel processors and processing
Matchballs --- a multi-agent-system for ontology-based collaborative learning games
CRIWG'12 Proceedings of the 18th international conference on Collaboration and Technology
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An organization is presented for implementing solutions to knowledge-based AI problems. The hypothesize-and-test paradigm is used as the basis for cooperation among many diverse and independent knowledge sources (KS's). The KS's are assumed individually to be errorful and incomplete. A uniform and integrated multi-level structure, the blackboard, holds the current state of the system. Knowledge sources cooperate by creating, accessing, and modifying elements in the blackboard. The activation of a KS is data-driven, based on the occurrence of patterns in the blackboard which match templates specified by the knowledge source. Each level in the blackboard specifies a different representation of the problem space; the sequence of levels forms a loose hierarchy in which the elements at each level can approximately be described as abstractions of elements at the next lower level. This decomposition can be thought of as an a prion framework of a plan for solving the problem; each level is a generic stage in the plan. The elements at each level in the blackboard are hypotheses about some aspect of that level. The internal structure of an hypothesis consists of a fixed set of attributes; this set is the same for hypotheses at all levels of representation in the blackboard. These attributes are selected to serve as mechanisms for implementing the data-directed hypothesize-and-test paradigm and for efficient goal-directed scheduling of KS's. Knowledge sources may create networks of structural relationships among hypotheses. These relationships, which are explicit in the blackboard, serve to represent inferences and deductions made by the KS's about the hypotheses; they also allow competing and overlapping partial solutions to be handled in an integrated manner. The Hearsay II speech-understanding system is an implementation of this organization; it is used here as an example for descriptive purposes.