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Virginia Tech

Evaluating the Effects of Automatic Speech Recognition Word Accuracy

Abstract

dc:description.abstract

Automatic Speech Recognition (ASR) research has been primarily focused towards large-scale systems and industry, while other areas that require attention are often over-looked by researchers. For this reason, this research looked at automatic speech recognition at the consumer level. Many individual consumers will purchase and use automatic software recognition for a different purpose than that of the military or commercial industries, such as telecommunications. Consumers who purchase the software for personal use will mainly use ASR for dictation of correspondences and documents. Two ASR dictation software packages were used to conduct the study. The research examined the relationships between (1) speech recognition software training and word accuracy, (2) error-correction time by the user and word accuracy, and (3) correspondence type and word accuracy. The correspondences evaluated were those that resemble Personal, Business, and Technical Correspondences. Word accuracy was assessed after initial system training, five minutes of error-correction time, and ten minutes of error-correction time. Results indicated that word recognition accuracy achieved does affect user satisfaction. It was also found that with increased error-correction time, word accuracy results improved. Additionally, the results found that Personal Correspondence achieved the highest mean word accuracy rate for both systems and that Dragon Systems achieved the highest mean word accuracy recognition for the Correspondences explored in this research. Results were discussed in terms of subjective and objective measures, advantages and disadvantages of speech input, and design recommendations were provided.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Industrial and Systems Engineering
Department dc:contributor.department
Industrial and Systems Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
1998

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Doe, Hope L.
Chair dc:contributor.committeechair
  • Kleiner, Brian M.
Committee members dc:contributor.committeemember
  • Williges, Robert C.
  • Gellatly, Andrew W.

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-7598-165040
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/36956

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Doe, Hope L.. Evaluating the Effects of Automatic Speech Recognition Word Accuracy. masters thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36956