Automatic speech recognition in the booth
Assessment of system performance, interpreters’ performances and interactions in the context of numbers
Published online: 26 November 2020
https://doi.org/10.1075/target.19166.def
https://doi.org/10.1075/target.19166.def
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.
Article outline
- 1.Introduction
- 2.Interpreting numbers
- 3.Methodology
- 3.1InterpretBank
- 3.2Preliminary test
- 3.3Equipment
- 3.4Participants
- 3.5Speeches
- 3.6Procedure
- 3.7Data processing and analysis
- 4.Results
- 4.1Findings regarding ASR
- 4.1.1Ergonomics
- 4.1.2Latency
- 4.1.3ASR precision for numbers
- 4.2Findings regarding presumed use of the ASR
- 4.3Findings regarding performance
- 4.3.1Renditions, ASR availability and presumed use
- 4.3.2Results per interpreter
- 4.3.3Renditions and number type
- 4.1Findings regarding ASR
- 5.Discussion
- 6.Conclusions
- Acknowledgements
- Notes
References
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