Semantic Processing for Speech Understanding

Abstract

This paper describes aspects of the semantic component of the speech understanding system currently being developed jointly by SRI and SDC. The semantic component consists of two major parts: a semantic network coding a model of the task domain and a battery of semantic composition routines (SCRs) that are coordinated with the language definition (i.e., the "grammar" for the speech understanding system). This paper concentrates exclusively on the interplay between these two major parts during parsing. However, the semantic component also plays important roles in knowledge management, discourse analysis, prediction, and question answering. The semantic component of the speech understanding system discussed here rules out phrase combinations that are not meaningful and produces semantic interpretations for combinations that are. The system consists of a semantic network model and routines that interact with it. The net is partitioned into a set of hierarchically ordered subnets, facilitating the encoding of higher-order predicates and the maintenance of multiple parsing hypotheses. Outputs from these routines are network fragments consisting of several subnets that in aggregate capture the interrelationships between a phrase's syntax and semantics.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1975
Accession Number
ADA458706

Entities

People

  • Gary G. Hendrix

Organizations

  • SRI International

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Applied Computer Science
  • Automated Speech Recognition
  • Coding
  • Computational Linguistics
  • Contracts
  • Grammars
  • Information Operations
  • Knowledge Management
  • Language
  • Linguistics
  • Natural Language Processing
  • Organizational Structure
  • Semantics
  • Words (Language)

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computer Science.
  • Mathematical Modeling and Probability Theory.