Ronnie W. Smith and D. Richard Hipp
- Published in print:
- 1995
- Published Online:
- November 2020
- ISBN:
- 9780195091878
- eISBN:
- 9780197560686
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780195091878.003.0008
- Subject:
- Computer Science, Human-Computer Interaction
Without development of an actual working system it is impossible to empirically validate the proposed computational model. Thus, the architecture introduced in section ...
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Without development of an actual working system it is impossible to empirically validate the proposed computational model. Thus, the architecture introduced in section 3.1 has been implemented on a Sun 4 workstation and later ported to a Spare II workstation. The majority of the code is written in Quintus Prolog while the parser is written in C. The system software is available via anonymous FTP as described in appendix C. The overall hardware configuration is illustrated in figure 6.1. Speech recognition is performed by a Verbex 6000 user-dependent connected-speech recognizer running on an IBM PC. The vocabulary is currently restricted to the 125 words given in table 7.1. Users are required to begin each utterance with the word “verbie” and end with the word “over” (e.g. “verbie, the switch is up, over”). The Verbex speech recognizer acknowledges each input with a small beep. These sentinel interactions act as a synchronization mechanism for the user arid the machine. Speech output is performed by a DECtalk DTCO1 text-to-speech converter. This chapter discusses the following technical aspects of the implementation. • The various knowledge representation formalisms. • The implemented domain processor, an expert system for assisting in simple circuit repair. • The implemented generation component. • The basic physical resource utilization of the system. The basis for the implementation has been the logic programming language, Prolog. Clocksin and Mellish [CM87] provide an introduction to this language. Pereira and Shieber [PS87] arid McCord [McC87] can be consulted for a discussion of the usage of Prolog for natural language analysis. Prolog allows the expression of rules and facts in a subset of first-order logic called Horn clauses. Prolog is supplemented with non-logical features that aid in efficient computation as well, but as a representational formalism, its utility in representing rules and facts in a declarative format provides a basis for the representation of knowledge and rules within the model. The Goal and Action Description Language was introduced in section 3.2.2. A detailed description is provided in appendix A. It is used as a standard formalism for representing goals that may be accomplished during a task.
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Without development of an actual working system it is impossible to empirically validate the proposed computational model. Thus, the architecture introduced in section 3.1 has been implemented on a Sun 4 workstation and later ported to a Spare II workstation. The majority of the code is written in Quintus Prolog while the parser is written in C. The system software is available via anonymous FTP as described in appendix C. The overall hardware configuration is illustrated in figure 6.1. Speech recognition is performed by a Verbex 6000 user-dependent connected-speech recognizer running on an IBM PC. The vocabulary is currently restricted to the 125 words given in table 7.1. Users are required to begin each utterance with the word “verbie” and end with the word “over” (e.g. “verbie, the switch is up, over”). The Verbex speech recognizer acknowledges each input with a small beep. These sentinel interactions act as a synchronization mechanism for the user arid the machine. Speech output is performed by a DECtalk DTCO1 text-to-speech converter. This chapter discusses the following technical aspects of the implementation. • The various knowledge representation formalisms. • The implemented domain processor, an expert system for assisting in simple circuit repair. • The implemented generation component. • The basic physical resource utilization of the system. The basis for the implementation has been the logic programming language, Prolog. Clocksin and Mellish [CM87] provide an introduction to this language. Pereira and Shieber [PS87] arid McCord [McC87] can be consulted for a discussion of the usage of Prolog for natural language analysis. Prolog allows the expression of rules and facts in a subset of first-order logic called Horn clauses. Prolog is supplemented with non-logical features that aid in efficient computation as well, but as a representational formalism, its utility in representing rules and facts in a declarative format provides a basis for the representation of knowledge and rules within the model. The Goal and Action Description Language was introduced in section 3.2.2. A detailed description is provided in appendix A. It is used as a standard formalism for representing goals that may be accomplished during a task.
