MANAGING MULTIPLE KNOWLEDGE SOURCES IN CONSTRAINT-BASED PARSING OF SPOKEN LANGUAGE

Article type: Research Article

Authors: Harper, Mary P. | Helzerman, Randall A.

Affiliations: School of Electrical Engineering, 1285 Electrical Engineering Building, Purdue University, West Lafayette, IN 47907-1285, USA. {harper, helz}@ecn.purdue.edu

Abstract: In this paper, we describe a system which is capable of utilizing a variety of knowledge sources to select the most appropriate parse for a spoken sentence. These knowledge sources include syntax, semantics, and contextual information. We discuss one way to utilize contextual information when determining the parse for a sentence. At its simplest level, the system can be thought of as a general-purpose query answering system for multiple topical databases. The user's input would be processed by the language processor which interfaces to the databases with the goal of interacting with the correct database in order to provide a reasonable answer to the user's spoken request. Initially, it analyzes a word graph of sentence hypotheses provided by a speech recognizer using general syntactic and semantic rules. Then, if the utterance is still ambiguous, it utilizes context-specific constraints to further refine the analysis. This brings us closer to developing a more general purpose interface for multiple databases.

DOI: 10.3233/FI-1995-232346

Journal: Fundamenta Informaticae, vol. 23, no. 2-4, pp. 303-353, 1995