Gruber T and Cohen P 1989, The design of an automated assistant for acquiring strategic knowledge, ACM SIGART Bulletin:108, (147-151), Online publication date: 1-Apr-1989 .

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.

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

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.

Sentences in first-order predicate logic can be usefully interpreted as programs. In this paper the operational and fixpoint semantics of predicate logic programs are defined, and the connections with the proof theory and model theory of logic are investigated. It is concluded that operational semantics is a part of proof theory and that fixpoint semantics is a special case of model-theoretic semantics.

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Computer-Based Medical Consultations: MYCIN focuses on MYCIN, a novel computer-based expert system designed to assist physicians with clinical decisions concerning the selection of appropriate therapy for patients with infections. It discusses medical computing, artificial intelligence, and the clinical problem areas for which the MYCIN program is designed, and it describes in detail how the MYCIN program helps physicians in making decisions. Comprised of seven chapters, this volume begins with an overview of MYCIN and the criteria used in its design. The book also explores MYCIN'S ability to answer questions with respect to its knowledge base and the details of a specific consultation, evaluation and future extensions of the MYCIN system, the limitations and accomplishments of MYCIN, and its contributions in artificial intelligence and computer-based medical decision making. This book is a valuable source of information for computer scientists and members of the medical community.

"The DENDRAL computer program uses established rules of molecular fragmentation to help chemists solve complex structural problems from mass spectral data. This paper describes a computer program called Meta-DENDRAL, that can aid in the discovery of such rules from empirical data on known components. The program uses heuristic methods to search for common structural environments around those bonds that are found to fragment and abstracts plausible fragmentation rules. The program has been tested on the well-characterized, low-resolution mass spectra of aliphatic amines and the high-resolution mass spectra of estrogenic steroids. The program has also discovered new fragmentation rules for mono-, di-, and triketoandrostanes."Journal of the American Chemical Society 98:6168-6178

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