Do face masks introduce bias in speech technologies? The case of automated scoring of speaking proficiency
This addresses concerns about fairness in speech technologies for language proficiency testing during the COVID-19 pandemic, but the findings are incremental as they show no significant impact.
The study investigated whether face masks bias automated scoring of English speaking proficiency by comparing test-takers wearing masks to a control group, finding that while masks caused acoustic and speech pattern differences, they did not affect human or automated scores, with no bias detected.
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.