Evaluating Spoken Language Interaction

Abstract

To study the spoken language interface in the context of a complex problem-solving task, a group of users were asked to perform a spreadsheet task, alternating voice and keyboard input. A total of 40 tasks were performed by each participant, the first thirty in a group (over several days), the remaining ones a month later. The voice spreadsheet program used in this study was extensively instrumented to provide detailed information about the components of the interaction. These data, as well as analysis of the participants's utterances and recognizer output, provide a fairly detailed picture of spoken language interaction. Although task completion by voice took longer than by keyboard, analysis shows that users would be able to per- form the spreadsheet task faster by voice, if two key criteria could be met: recognition occurs in real-time, and the error rate is sufficiently low. This initial experience with a spoken language system also allows us to identify several metrics, beyond those traditionally associated with speech recognition, that can be used to characterize system performance.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1989
Accession Number
ADA458663

Entities

People

  • Alexander I. Rudnicky
  • Joseph H. Polifroni
  • Michelle Sakamoto

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Automated Speech Recognition
  • Computer Science
  • Computers
  • Errors
  • Experimental Data
  • Keyboards
  • Language
  • Natural Language Processing
  • Natural Languages
  • Noise
  • Recognition
  • Resource Management
  • Signal Processing
  • Spreadsheet Software
  • Task Performance And Analysis
  • Test Sets

Readers

  • Computational Modeling and Simulation
  • Speech Processing/Speech Recognition.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation