Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
1 file | 1.48 MB
Add to list
  1. Search results
  2. Automatic speech recognition in the b...

Automatic speech recognition in the booth : assessment of system performance, interpreters’ performances and interactions in the context of numbers

Bart Defrancq (UGent) and Claudio Fantinuoli
(2021) TARGET-INTERNATIONAL JOURNAL OF TRANSLATION STUDIES. 33(1). p.73-102
Author
Organization
Abstract
Automatic Speech Recognition (ASR) has been proposed as a means to enhance state-of-the-art computer-assisted interpreting (CAI) tools and to allow machine-learning techniques to enter the workflow of professional interpreters. In this article, we test the usefulness of real-time transcription with number highlighting of a source speech for simultaneous interpreting using InterpretBank ASR. The system's precision is high (96%) and its latency low enough to fit interpreters' ear-voice span (EVS). We evaluate the potential benefits among first-time users of this technology by applying an error matrix and by investigating the users' subjective perceptions through a questionnaire. The results show that the ASR provision improves overall performance for almost all number types. Interaction with the ASR support is varied and participants consult it for just over half of the stimuli. The study also provides some evidence of the psychological benefits of ASR availability and of overreliance on ASR support.
Keywords
Linguistics and Language, Communication, Language and Linguistics, automatic speech recognition, simultaneous interpreting, rendition of numbers, computer-assisted interpreting

Downloads

  • Download
    (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 1.48 MB

Citation

Please use this url to cite or link to this publication:

MLA
Defrancq, Bart, and Claudio Fantinuoli. “Automatic Speech Recognition in the Booth : Assessment of System Performance, Interpreters’ Performances and Interactions in the Context of Numbers.” TARGET-INTERNATIONAL JOURNAL OF TRANSLATION STUDIES, vol. 33, no. 1, 2021, pp. 73–102, doi:10.1075/target.19166.def.
APA
Defrancq, B., & Fantinuoli, C. (2021). Automatic speech recognition in the booth : assessment of system performance, interpreters’ performances and interactions in the context of numbers. TARGET-INTERNATIONAL JOURNAL OF TRANSLATION STUDIES, 33(1), 73–102. https://doi.org/10.1075/target.19166.def
Chicago author-date
Defrancq, Bart, and Claudio Fantinuoli. 2021. “Automatic Speech Recognition in the Booth : Assessment of System Performance, Interpreters’ Performances and Interactions in the Context of Numbers.” TARGET-INTERNATIONAL JOURNAL OF TRANSLATION STUDIES 33 (1): 73–102. https://doi.org/10.1075/target.19166.def.
Chicago author-date (all authors)
Defrancq, Bart, and Claudio Fantinuoli. 2021. “Automatic Speech Recognition in the Booth : Assessment of System Performance, Interpreters’ Performances and Interactions in the Context of Numbers.” TARGET-INTERNATIONAL JOURNAL OF TRANSLATION STUDIES 33 (1): 73–102. doi:10.1075/target.19166.def.
Vancouver
1.
Defrancq B, Fantinuoli C. Automatic speech recognition in the booth : assessment of system performance, interpreters’ performances and interactions in the context of numbers. TARGET-INTERNATIONAL JOURNAL OF TRANSLATION STUDIES. 2021;33(1):73–102.
IEEE
[1]
B. Defrancq and C. Fantinuoli, “Automatic speech recognition in the booth : assessment of system performance, interpreters’ performances and interactions in the context of numbers,” TARGET-INTERNATIONAL JOURNAL OF TRANSLATION STUDIES, vol. 33, no. 1, pp. 73–102, 2021.
@article{8704773,
  abstract     = {{Automatic Speech Recognition (ASR) has been proposed as a means to enhance state-of-the-art computer-assisted interpreting (CAI) tools and to allow machine-learning techniques to enter the workflow of professional interpreters. In this article, we test the usefulness of real-time transcription with number highlighting of a source speech for simultaneous interpreting using InterpretBank ASR. The system's precision is high (96%) and its latency low enough to fit interpreters' ear-voice span (EVS). We evaluate the potential benefits among first-time users of this technology by applying an error matrix and by investigating the users' subjective perceptions through a questionnaire. The results show that the ASR provision improves overall performance for almost all number types. Interaction with the ASR support is varied and participants consult it for just over half of the stimuli. The study also provides some evidence of the psychological benefits of ASR availability and of overreliance on ASR support.}},
  author       = {{Defrancq, Bart and Fantinuoli, Claudio}},
  issn         = {{0924-1884}},
  journal      = {{TARGET-INTERNATIONAL JOURNAL OF TRANSLATION STUDIES}},
  keywords     = {{Linguistics and Language,Communication,Language and Linguistics,automatic speech recognition,simultaneous interpreting,rendition of numbers,computer-assisted interpreting}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{73--102}},
  title        = {{Automatic speech recognition in the booth : assessment of system performance, interpreters’ performances and interactions in the context of numbers}},
  url          = {{http://doi.org/10.1075/target.19166.def}},
  volume       = {{33}},
  year         = {{2021}},
}
Altmetric
View in Altmetric
Web of Science
Times cited: