Accession Number:

ADA255865

Title:

Talking to InterFIS: Adding Speech Input to a Natural Language Interface

Descriptive Note:

Research rept.

Corporate Author:

NAVAL RESEARCH LAB WASHINGTON DC CENTER FOR APPLIED RESEARCH IN ARTIFICIAL INTELLIGENCE

Report Date:

1992-09-11

Pagination or Media Count:

15.0

Abstract:

InterFIS is a natural language interface to the troubleshooting module of the Fault Isolation Shell FIS, which is an expert system development tool for the diagnosis of failures in analog electronics equipment. The main functions of this FIS module are as follows 1 to compute the probability that a particular fault hypothesis is correct after one or more tests have been performed on a particular piece of electronics equipment, and 2 to recommend the next best test based on information supplied by the diagnostician during a testing session. The original interface to FIS was standard keyboard input, where the appropriate abbreviations for all commands were displayed on the screen in a large list grouped by function. A simple graphic interface also was developed, where the user invoked the commands by clicking on screen buttons labeled according to their functional grouping. Later a natural language interface, InterFIS, was added. InterFIS is a natural language understanding interface that accepts typed English commands as input. The PROTEUS chart parser performs a syntactic analysis, producing an application-independent syntactic representation of the input sentence. This intermediate representation is mapped to domain-specific verb models by the semantic interpreter PFQAS and then converted to FIS commands by the command translator COIN. The main drawback to this interface is that typing English sentences is slow and requires the use of both hands. This report discusses the addition of speech recognition capabilities to InterFIS. Because of the limitations of todays speech recognition technology, the addition of this capability affects the structure and flexibility of the interface. The report describes the speech recognition module, and provides a brief evaluation of its performance.

Subject Categories:

  • Linguistics
  • Computer Programming and Software
  • Cybernetics
  • Electrical and Electronic Equipment

Distribution Statement:

APPROVED FOR PUBLIC RELEASE