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San Francisco: Freeman

One of the major stumbling blocks to more effective used computers by naive users is the lack of natural means of communication between the user and the computer system. As such this work falls somewhere between highly constrained formal language query systems and unrestricted natural language under-standing systems. The primary purpose of this research is not to advance our theoretical under-standing of natural language but rather to put forth a set of techniques for embedding both semantic/conceptual and pragmatic information into a useful natural language interface module. Our intent has been to produce a front end system which enables the user to concentrate on his problem or task rather than making him worry about how to communicate his ideas or questions to the machine.

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A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

New York: North-Holland

This paper presents a functional overview of the features and capabilities of QLISP, one of the newest of the current generation of very high level languages developed for use in Artificial Intelligence (AI) research.QLISP is both a programming language and an interactive programming environment. It embeds an extended version of QA4, an earlier AI language, in INTERLISP, a widely available version of LISP with a variety of sophisticated programming aids.The language features provided by QLISP include a variety of useful data types, an associative data base for the storage and retrieval of expressions, the ability to associate property lists with arbitrary expressions, a powerful pattern matcher based on a unification algorithm, pattern-directed function invocation, "teams" of pattern invoked functions, a sophisticated mechanism for breaking a data base into contexts, generators for associative data retrieval, and easy extensibility.System features available in QLISP include a very smooth interaction with the underlying INTERLISP language, a facility for aggregating multiple pattern matches, and features for interactive control of programs.A number of applications to which QLISP has been put are briefly discussed, and some directions for future development are presented. SRI Tech.Note 120, AI Center, SRI International, Inc., Menlo Park, Calif.

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.