Literaturnachweis - Detailanzeige
Autor/inn/en | Jannetts, Stephen; Schaeffler, Felix; Beck, Janet; Cowen, Steve |
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Titel | Assessing Voice Health Using Smartphones: Bias and Random Error of Acoustic Voice Parameters Captured by Different Smartphone Types |
Quelle | In: International Journal of Language & Communication Disorders, 54 (2019) 2, S.292-305 (14 Seiten)
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Zusatzinformation | ORCID (Jannetts, Stephen) |
Sprache | englisch |
Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
ISSN | 1368-2822 |
DOI | 10.1111/1460-6984.12457 |
Schlagwörter | Voice Disorders; Handheld Devices; Acoustics; Assistive Technology; Reliability; Measurement Techniques |
Abstract | Background: Occupational voice problems constitute a serious public health issue with substantial financial and human consequences for society. Modern mobile technologies such as smartphones have the potential to enhance approaches to prevention and management of voice problems. This paper addresses an important aspect of smartphone-assisted voice care: the reliability of smartphone-based acoustic analysis for voice health state monitoring. Aim: To assess the reliability of acoustic parameter extraction for a range of commonly used smartphones by comparison with studio recording equipment. Methods & Procedures: Twenty-two vocally healthy speakers (12 female, 10 male) were recorded producing sustained vowels and connected speech under studio conditions using a high-quality studio microphone and an array of smartphones. For both types of utterance, Bland-Altman analysis was used to assess overall reliability for mean F0, cepstral peak prominence (CPPS), Jitter (RAP) and Shimmer %. Outcomes & Results: Analysis of the systematic and random error indicated significant bias for CPPS across both sustained vowels and passage reading. Analysis of the random error of the devices indicated that that mean F0 and CPPS showed acceptable random error size, while jitter and shimmer random error was judged as problematic. Conclusions & Implications: Confidence in the feasibility of smartphone-based voice assessment is increased by the experimental finding of high levels of reliability for some clinically relevant acoustic parameters, while the use of other parameters is discouraged. We also challenge the practice of using statistical tests (e.g., t-tests) for measurement reliability assessment. (As Provided). |
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Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
Update | 2020/1/01 |