Effects of face masks on speech recognition in multi-talker babble noise

PLoS One. 2021 Feb 24;16(2):e0246842. doi: 10.1371/journal.pone.0246842. eCollection 2021.

Abstract

Face masks are an important tool for preventing the spread of COVID-19. However, it is unclear how different types of masks affect speech recognition in different levels of background noise. To address this, we investigated the effects of four masks (a surgical mask, N95 respirator, and two cloth masks) on recognition of spoken sentences in multi-talker babble. In low levels of background noise, masks had little to no effect, with no more than a 5.5% decrease in mean accuracy compared to a no-mask condition. In high levels of noise, mean accuracy was 2.8-18.2% lower than the no-mask condition, but the surgical mask continued to show no significant difference. The results demonstrate that different types of masks generally yield similar accuracy in low levels of background noise, but differences between masks become more apparent in high levels of noise.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Auditory Perception / physiology*
  • COVID-19 / prevention & control
  • COVID-19 / psychology
  • COVID-19 / transmission
  • Female
  • Humans
  • Language
  • Male
  • Masks* / adverse effects
  • N95 Respirators / adverse effects
  • Noise
  • SARS-CoV-2 / isolation & purification
  • Speech / physiology
  • Speech Perception / physiology*

Grants and funding

This material is based on upon work supported by the National Science Foundation under Grant No. 1945069 awarded to JCT. This work received funding from Villanova University’s Falvey Memorial Library Scholarship Open Access Reserve (SOAR) Fund awarded to JCT and CMT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.