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      Speaking with a KN95 face mask: a within-subjects study on speaker adaptation and strategies to improve intelligibility

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          Abstract

          Mask-wearing during the COVID-19 pandemic has prompted a growing interest in the functional impact of masks on speech and communication. Prior work has shown that masks dampen sound, impede visual communication cues, and reduce intelligibility. However, more work is needed to understand how speakers change their speech while wearing a mask and to identify strategies to overcome the impact of wearing a mask. Data were collected from 19 healthy adults during a single in-person session. We investigated the effects of wearing a KN95 mask on speech intelligibility, as judged by two speech-language pathologists, examined speech kinematics and acoustics associated with mask-wearing, and explored KN95 acoustic filtering. We then considered the efficacy of three speaking strategies to improve speech intelligibility: Loud, Clear, and Slow speech. To inform speaker strategy recommendations, we related findings to self-reported speaker effort. Results indicated that healthy speakers could compensate for the presence of a mask and achieve normal speech intelligibility. Additionally, we showed that speaking loudly or clearly—and, to a lesser extent, slowly—improved speech intelligibility. However, using these strategies may require increased physical and cognitive effort and should be used only when necessary. These results can inform recommendations for speakers wearing masks, particularly those with communication disorders (e.g., dysarthria) who may struggle to adapt to a mask but can respond to explicit instructions. Such recommendations may further help non-native speakers and those communicating in a noisy environment or with listeners with hearing loss.

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          The Research Electronic Data Capture (REDCap) data management platform was developed in 2004 to address an institutional need at Vanderbilt University, then shared with a limited number of adopting sites beginning in 2006. Given bi-directional benefit in early sharing experiments, we created a broader consortium sharing and support model for any academic, non-profit, or government partner wishing to adopt the software. Our sharing framework and consortium-based support model have evolved over time along with the size of the consortium (currently more than 3200 REDCap partners across 128 countries). While the "REDCap Consortium" model represents only one example of how to build and disseminate a software platform, lessons learned from our approach may assist other research institutions seeking to build and disseminate innovative technologies.
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            A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research.

            Intraclass correlation coefficient (ICC) is a widely used reliability index in test-retest, intrarater, and interrater reliability analyses. This article introduces the basic concept of ICC in the content of reliability analysis.
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              lmerTest Package: Tests in Linear Mixed Effects Models

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                Author and article information

                Contributors
                gutz@g.harvard.edu
                hrowe@mghihp.edu
                vbolowsky@mghihp.edu
                jgreen2@mghihp.edu
                Journal
                Cogn Res Princ Implic
                Cogn Res Princ Implic
                Cognitive Research: Principles and Implications
                Springer International Publishing (Cham )
                2365-7464
                30 July 2022
                30 July 2022
                December 2022
                : 7
                : 73
                Affiliations
                [1 ]GRID grid.38142.3c, ISNI 000000041936754X, Program in Speech and Hearing Bioscience and Technology, , Harvard Medical School, ; Boston, MA USA
                [2 ]GRID grid.429502.8, ISNI 0000 0000 9955 1726, Department of Communication Sciences and Disorders, , MGH Institute of Health Professions, ; Building 79/96, 2nd floor, 13th Street, Boston, MA 02129 USA
                Article
                423
                10.1186/s41235-022-00423-4
                9339031
                35907167
                b834e2bd-9b4d-471c-b2d3-cffb829cab54
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 October 2021
                : 18 July 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000055, National Institute on Deafness and Other Communication Disorders;
                Award ID: K24DC016312
                Award ID: F31DC019016
                Award ID: T32DC000038
                Award Recipient :
                Categories
                Original Article
                Custom metadata
                © The Author(s) 2022

                face masks,speaker adaptation,compensation,speaker strategies

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