In Davis and Lenat (1980). Memo AIM-283, AILaboratory,and Rep.No.STAN-CS-76-552, Computer Science Dept., Stanford University.

The Harpy connected speech recognition system is the result of an attempt to understand the relative importance of various design choices of two earlier speech recognition systems developed at Carnegie-Mellon University: The Hearsay-1 system and the Dragon system. Knowledge is represented in the Hearsay-1 system as procedures and in the Dragon system as a Markov network with a-priori transition probabilities between states. Systematic performance analysis of various design choices of these two systems resulted in the HARPY system, in which knowledge is represented as a finite state transition network but without the a-priori transition probabilities. Harpy searches only a few'best' syntactic (and acoustic) paths in parallel to determine the optimal path, and uses segmentation to effectively reduce the utterance length, thereby reducing the number of state probability updates that must be done. Several new heuristics have been added to the HARPY system to improve its performance and speed: detection of common sub-nets and collapsing them to reduce overall network size and complexity, eliminating the need for doing an acoustic match for all phonemic types at every time sample, and semi-automatic techniques for learning the lexical representations (that are needed for a steady-state system of this type) and the phonemic templates from training data, thus automatically accounting for the commonly occurring intra-word coarticulation and juncture phenomena.

Boitet, C. 1977 Where Does GETA Stand at the Beginning of Brinkmann, K.-H.

A generalization of AND/OR graphs is introduced as a problem solving model, in which subproblem interdependence in problem reduction can be explicitly accounted for. An ordered-search algorithm is given to find a solution. The algorithm is proven to be admissible and optimal. Examples are given which show the application of the formalism to problems which cannot be modelled by AND/OR graphs. Generalized AND/OR graphs are finally shown to be equivalent to type O grammars.

This text is a description of a computer-based system designed to assist physicians with clinical decision-making. This system, termed MYCIN, utilizes computer techniques derived principally from the subfield of computer science known as artificial intelligence (AI). MYCIN's task is to assist with the decisions involved in the selection of appropriate therapy for patients with infections.

MYCIN contains considerable medical expertise and is also a novel application of computing technology. Thus, this text is addressed both to members of the medical community, who may have limited computer science backgrounds, and to computer scientists with limited knowledge of medical computing and clinical medicine. Some sections of the text may be of greater interest to one community than to the other. A guide to the text follows so that you may select those portions most pertinent to your particular interests and background.

The complete book in a single file.

Book form of Shortliffe's Ph.D. dissertation in medical informatics. New York: American Elsevier.

In L. Steels (Ed.), Advances in natural language processing. Antwerp, Belgium: University of Antwerp.

As a field, artificial intelligence has always been on the border of respectability, and therefore on the border of crackpottery. Many critics (Dreyfus, 1972), (Lighthill, 1973) have urged that we are over the border. We have been very defensive toward this charge, drawing ourselves up with dignity when it is made and folding the cloak of Science about us. On the other hand, in private, we have been justifiably proud of our willingness to explore weird ideas, because pursuing them is the only way to make progress.

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A YOUNG MAN, WHO HAS OLIGURIA. IT HAS BEEN DENIED THAT HE HAS RECENT SCARLET FEVER. HE HAS NOT-RECEIVED RADIOGRAPHIC CONTRAST MATERIAL. HE HAS NOT-RECEIVED NEPHROTOXIC DRUGS. HE HAS MODERATELY-ELEVATED URINE SODIUM.