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Electrical Engineering and Systems Science > Audio and Speech Processing

arXiv:2008.07520 (eess)
COVID-19 e-print

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[Submitted on 17 Aug 2020 (v1), last revised 3 Nov 2020 (this version, v2)]

Title:Do face masks introduce bias in speech technologies? The case of automated scoring of speaking proficiency

Authors:Anastassia Loukina, Keelan Evanini, Matthew Mulholland, Ian Blood, Klaus Zechner
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Abstract:The COVID-19 pandemic has led to a dramatic increase in the use of face masks worldwide. Face coverings can affect both acoustic properties of the signal as well as speech patterns and have unintended effects if the person wearing the mask attempts to use speech processing technologies. In this paper we explore the impact of wearing face masks on the automated assessment of English language proficiency. We use a dataset from a large-scale speaking test for which test-takers were required to wear face masks during the test administration, and we compare it to a matched control sample of test-takers who took the same test before the mask requirements were put in place. We find that the two samples differ across a range of acoustic measures and also show a small but significant difference in speech patterns. However, these differences do not lead to differences in human or automated scores of English language proficiency. Several measures of bias showed no differences in scores between the two groups.
Subjects: Audio and Speech Processing (eess.AS); Computation and Language (cs.CL); Human-Computer Interaction (cs.HC); Sound (cs.SD)
Cite as: arXiv:2008.07520 [eess.AS]
  (or arXiv:2008.07520v2 [eess.AS] for this version)
  https://doi.org/10.48550/arXiv.2008.07520
Journal reference: Proceedings of Interspeech 2020, 1942-1946
Related DOI: https://doi.org/10.21437/Interspeech.2020-1264

Submission history

From: Anastassia Loukina [view email]
[v1] Mon, 17 Aug 2020 17:58:29 UTC (69 KB)
[v2] Tue, 3 Nov 2020 16:10:15 UTC (69 KB)
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