Effects of face masks on speech recognition in multi-talker babble noise.
PLoS One
; 16(2): e0246842, 2021.
Article
in English
| MEDLINE | ID: covidwho-1099924
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.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Auditory Perception
/
Speech Perception
/
Masks
Type of study:
Experimental Studies
/
Qualitative research
Limits:
Adult
/
Female
/
Humans
/
Male
Language:
English
Journal:
PLoS One
Journal subject:
Science
/
Medicine
Year:
2021
Document Type:
Article
Affiliation country:
Journal.pone.0246842
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