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

Título

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

Autor

Joseph C Toscano, Cheyenne M Toscano

Descripción

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.

Fecha

2021

Identificador

10.1371/journal.pone.0246842

Fuente

Epidemiology and Health

Editor

Korean Society of Epidemiology

Cobertura

Science, Medicine

Archivos

https://socictopen.socict.org/files/to_import/pdfs/00dc93fba7c1f67c73dea919ae2285ce.pdf

Colección

Citación

Joseph C Toscano, Cheyenne M Toscano, “Effects of face masks on speech recognition in multi-talker babble noise.,” SOCICT Open, consulta 19 de abril de 2026, https://www.socictopen.socict.org/items/show/4675.

Formatos de Salida

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