Title page for ETD etd-2737102539751141


Type of Document Dissertation
Author Gellatly, Andrew William
Author's Email Address gellatly@ctr.vt.edu
URN etd-2737102539751141
Title The Use of Speech Recognition Technology in Automotive Applications
Degree PhD
Department Industrial and Systems Engineering
Advisory Committee
Advisor Name Title
Casali, John G.
Kiefer, Raymond J.
Kleiner, Brian M.
Williges, Robert C.
Dingus, Thomas A. Committee Chair
Keywords
  • driver behavior
  • dual-task performance
  • decision tools
Date of Defense 1997-03-28
Availability unrestricted
Abstract
The research objectives were (1) to perform a detailed

review of the literature on speech recognition technology

and the attentional demands of driving; (2) to develop

decision tools that assist designers of in-vehicle systems;

(3) to experimentally examine automatic speech recognition

(ASR) design parameters, input modalities, and driver

ages; and (4) to provide human factors recommendations

for the use of speech recognition technology in automotive

applications. Two experiments were conducted to

determine the effects of ASR design parameters, input

modality, and age on driving performance, system usability,

and driver preference/acceptance. Eye movement

behavior, steering input behavior, speed maintenance

behavior, reaction time to forward scene event, task

completion time, and task completion errors when driving

and performing in-vehicle tasks were measured. Driver

preference/acceptance subjective data were also recorded.

The results showed that ASR design parameters

significantly affected measures of driving performance,

system usability, and driver preference/acceptance.

However, from a practical viewpoint, ASR design

parameters had a nominal effect on driving performance.

Differences measured in driving performance brought on by

changes in ASR system design parameters were small

enough that alternative ASR system designs could be

considered without impacting driving performance. No

benefits could be claimed for ASR systems improving

driving safety/performance compared to current

manual-control systems. Speech recognition system design

demonstrated a moderate influence on the usability of

in-vehicle tasks. Criteria such as task completion times and

task completion errors were shown to be different between

speech-input and manual-input control methods, and under

different ASR design configurations. Therefore, trade-offs

between ASR system designs, and between speech-input

and manual-input systems, could be evaluated in terms of

usability. Finally, ASR system design had a nominal effect

on driver preference/acceptance. Further research is

warranted to determine if long-term use of ASR systems

with less than optimal design parameters would result in

significantly lower values for driver preference/acceptance

compared to data collected in this research effort. Human

factors recommendations for the use of ASR technology in

automotive applications are included. The

recommendations are based on the empirical research and

the literature review on speech recognition technology and

the attentional demands of driving.

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