User Interface Design for Voice Control Systems

  title={User Interface Design for Voice Control Systems},
  author={Wolfgang Tschirk},
A voice control system converts spoken commands into control actions, a process which is always imperfect due to errors of the speech recognizer. Most speech recognition research is focused on decreasing the recognizers’ error rates; comparatively little effort was spent to find interface designs that optimize the overall system, given a fixed speech recognizer performance. In order to evaluate such designs prior to their implementation and test, three components are required: 1) an appropriate… 

Tables from this paper

Self-optimizing voice control user interface

  • W. Tschirk
  • Computer Science
    2004 12th European Signal Processing Conference
  • 2004
A unified view on the recognition act is introduced, i.e. the classification of an incoming sound pattern, and a self-optimization algorithm for the user interface is derived, which minimizes the number of errors visible on theuser interface, given a fixed speech recognizer performance.

Not-so Easy Listening: Roots and Repercussions of Auditory Choice Difficulty in Voice Commerce

In the context of voice shopping, fifteen experiments demonstrate that information presented by voice can be more difficult to process than the same information presented in writing. Consequently,



Neural net speech recognizers — Voice remote control devices for disabled people

Reliable real world speech recognition is still a non-trivial task. One of the most challenging applications is voice control for disabled people. For many users of such a system, voice is the only

Computer-aided analysis and design for spoken dialogue systems based on quantitative simulations

A complete development of computer-aided analysis and design approaches for spoken dialogue systems based on quantitative simulations is presented, such that the behavior and performance of the dialogue system can be well predicted and efficiently analyzed before the implementation of the real spoken dialogue system is completed.

Rejection techniques for digit recognition in telecommunication applications

  • L. VillarrubiaA. Acero
  • Economics, Education
    1993 IEEE International Conference on Acoustics, Speech, and Signal Processing
  • 1993
The authors describe a technique for nonkeyword rejection and evaluate it in the context of an audiotex service using the ten Spanish digits to reduce the total cost function on the audiotext application.

The thoughtful elephant: strategies for spoken dialog systems

The system architecture caters to incorporating application specific knowledge, including, for example, database constraints, in the determination of the best sentence hypothesis for a user turn, and it is demonstrated how combination decisions over several turns can be exploited to boost the recognition performance of the system.

Data collection and performance evaluation of spoken dialogue systems: the MIT experience

This paper describes two understanding metrics called query density and concept efficiency which can be interpreted on a perutterance basis, but which are measured over the course of a dialogue.

Mathematical analysis of dialogue control strategies

A quantitative relation between the e ciency of dialogue control strategies, measured by the average number of exchanges taken during a dialogue, and the performance of a speech recognition system used in a spoken dialogue system is described.

Fundamentals of speech recognition

This book presents a meta-modelling framework for speech recognition that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of manually modeling speech.

Probability, random variables and stochastic processes

  • J. Proakis
  • Mathematics
    IEEE Trans. Acoust. Speech Signal Process.
  • 1985

Special issue on automatic speech recognition for mobile and portable devices

  • IEEE Transactions on Speech and Audio Processing vol. 10, no. 8, pp. 529-658, November 2002.
  • 2002

Special section on robust speech recognition

  • IEEE Transactions on Speech and Audio Processing vol. 2, no. 4, pp. 549-643, October 1994.
  • 1994