Acoustic Effect of Face Mask Design and Material Choice

Influence of face masks on recalibration of phonetic categories

Previous research demonstrates listeners dynamically adjust phonetic categories in line with lexical context. While listeners show flexibility in adapting speech categories, recalibration may be constrained when variability can be attributed externally. It has been hypothesized that when listeners attribute atypical speech input to a causal factor, phonetic recalibration is attenuated. The current study investigated this theory directly by examining the influence of face masks, an external factor that affects both visual and articulatory cues, on the magnitude of phonetic recalibration. Across four experiments, listeners completed a lexical decision exposure phase in which they heard an ambiguous sound in either /s/-biasing or /ʃ/-biasing lexical contexts, while simultaneously viewing a speaker with a mask off, mask on the chin, or mask over the mouth. Following exposure, all listeners completed an auditory phonetic categorization test along an /ʃ/-/s/ continuum. In Experiment 1 (when no face mask was present during exposure trials), Experiment 2 (when the face mask was on the chin), Experiment 3 (when the face mask was on the mouth during ambiguous items), and Experiment 4 (when the face mask was on the mouth during the entire exposure phase), listeners showed a robust and equivalent phonetic recalibration effect. Recalibration manifested as greater proportion /s/ responses for listeners in the /s/-biased exposure group, relative to listeners in the /ʃ/-biased exposure group. Results support the notion that listeners do not causally attribute face masks with speech idiosyncrasies, which may reflect a general speech learning adjustment during the COVID-19 pandemic.

Speaking with mask in the COVID-19 era: Multiclass machine learning classification of acoustic and perceptual parameters

The intensive use of personal protective equipment often requires increasing voice intensity, with possible development of voice disorders. This paper exploits machine learning approaches to investigate the impact of different types of masks on sustained vowels /a/, /i/, and /u/ and the sequence /a'jw/ inside a standardized sentence. Both objective acoustical parameters and subjective ratings were used for statistical analysis, multiple comparisons, and in multivariate machine learning classification experiments. Significant differences were found between mask+shield configuration and no-mask and between mask and mask+shield conditions. Power spectral density decreases with statistical significance above 1.5 kHz when wearing masks. Subjective ratings confirmed increasing discomfort from no-mask condition to protective masks and shield. Machine learning techniques proved that masks alter voice production: in a multiclass experiment, random forest (RF) models were able to distinguish amongst seven masks conditions with up to 94% validation accuracy, separating masked from unmasked conditions with up to 100% validation accuracy and detecting the shield presence with up to 86% validation accuracy. Moreover, an RF classifier allowed distinguishing male from female subject in masked conditions with 100% validation accuracy. Combining acoustic and perceptual analysis represents a robust approach to characterize masks configurations and quantify the corresponding level of discomfort.

Mask-Wearing Behaviors after Two Years of Wearing Masks Due to COVID-19 in Korea: A Cross-Sectional Study

In Korea, wearing masks in public places has become the norm during the prolonged coronavirus disease 2019 (COVID-19) pandemic. This cross-sectional study investigated the mask-wearing behavior of Koreans (n = 433) via online mode living in Seoul and Gwangju after wearing a mask in public spaces for two years due to COVID-19. The respondents selected their face masks based on season, gender, age, occupation, mask-wearing hours, mask filter performance, mask shape, and mask color. The general discomfort caused by wearing a mask was divided into physical and speech discomfort, and it was not correlated with anxiety when not wearing a face mask. Speech discomfort caused by wearing a mask was correlated with general discomfort, clear speech, vocal pain, anxiety, and only-indoor mask-off plans. Anxiety when not wearing a mask appeared to affect both indoor and outdoor mask-off plans. The more uncomfortable and less anxious respondents were when not wearing a mask, the sooner they wanted to discontinue wearing masks indoors and outdoors. It is expected that the use of masks will continue in the future and that there may be differences in the place and time of use of masks in Korea and around the world due to new infectious diseases and fine dust. Facial masks can be worn more comfortably and conveniently if the discomfort and anxiety of wearing a mask are improved by considering various behaviors when wearing a mask in the future.

Improving the measurement and acoustic performance of transparent face masks and shields

Opaque face masks harm communication by preventing speech-reading (lip-reading) and attenuating high-frequency sound. Although transparent masks and shields (visors) with clear plastic inserts allow speech-reading, they usually create more sound attenuation than opaque masks. Consequently, an iterative process was undertaken to create a better design, and the instructions to make it are published. The experiments showed that lowering the mass of the plastic inserts decreases the high-frequency sound attenuation. A shield with a clear thermoplastic polyurethane (TPU) panel had an insertion loss of (2.0 ± 1.1) dB for 1.25-8 kHz, which improves on previous designs that had attenuations of 11.9 dB and above. A cloth mask with a TPU insert was designed and had an insertion loss of (4.6 ± 2.3) dB for 2-8 kHz, which is better than the 9-22 dB reported previously in the literature. The speech intelligibility index was also evaluated. Investigations to improve measurement protocols that use either mannikins or human talkers were undertaken. Manufacturing variability and inconsistency of human speaking were greater sources of experimental error than fitting differences. It was shown that measurements from a mannikin could match those from humans if insertion losses from four human talkers were averaged.

The Influence of Face Masks on Verbal Communication in Persian in the Presence of Background Noise in Healthcare Staff

Wearing face masks has resulted in verbal communication being more challenging during the COVID-19 pandemic. This study aimed to investigate the effect of face masks on the speech comprehensibility of Persian nurses in healthcare settings. Twenty female nurses from the governmental hospitals randomly participated in an experiment on seven typical commercial face masks at two background noise levels. Nurses' speech intelligibility from a human talker when wearing each face mask was determined based on the speech discrimination score. The vocal effort of nurses wearing each face mask was determined based on the Borg CR10 scale. Based on the linear mixed model, the speech intelligibility of nurses from a human speaker wearing surgical masks, N95 masks, and a shield with face masks were approximately 10%, 20%, and 40-50% lower, respectively, than no-mask conditions (p < 0.01). The background noise decreased the speech intelligibility of nurses by approximately 22% (p < 0.01). The use of a face shield further decreased speech intelligibility up to 30% compared to using a face mask alone (p < 0.01). The vocal efforts of nurses when wearing surgical masks were not significant compared with the baseline vocal efforts (p > 0.05); however, vocal efforts of nurses when wearing N95 and N99 respirators were at an unacceptable level. The face masks had no considerable effect on the speech spectrum below 2.5 kHz; however, they reduced high frequencies by different values. Wearing face masks has a considerable impact on the verbal communication of nurses in Persian. The level of background noise in the healthcare setting can aggravate the effect sizes of face masks on speech comprehensibility.