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    Reliability of clinical voice parameters captured with smartphones – measurements of added noise and spectral tilt

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    Accepted Version (507.3Kb)
    Date
    2019-09-20
    Author
    Schaeffler, Felix
    Jannetts, Stephen
    Beck, Janet M.
    Metadata
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    Citation
    Schaeffler, F., Jannetts, S. & Beck, J. M. (2019) Reliability of clinical voice parameters captured with smartphones – measurements of added noise and spectral tilt. In: Proceedings of the 20th Annual Conference of the International Speech Communication Association INTERSPEECH, Graz, Austria, 15-19 September 2019, pp. 2523-2527.
    Abstract
    Smartphones have become powerful tools for data capture due to their computational power, internet connectivity, high quality sensors and user-friendly interfaces. This also makes them attractive for the recording of voice data that can be analysed for clinical or other voice health purposes. This however requires detailed assessment of the reliability of voice parameters extracted from smartphone recordings. In a previous study we analysed reliability of measures of periodicity and periodicity deviation, with very mixed results across parameters. In the present study we extended this analysis to measures of added noise and spectral tilt. We analysed systematic and random error for six frequently used acoustic parameters in clinical acoustic voice quality analysis. 22 speakers recorded sustained [a] and a short passage with a studio microphone and four popular smartphones simultaneously. Acoustic parameters were extracted with Praat and smartphone recordings were compared to the studio microphone. Results indicate a small systematic error for almost all parameters and smartphones. Random errors differed substantially between parameters. Our results suggest that extraction of acoustic voice parameters with mobile phones is not without problems and different parameters show substantial differences in reliability. Careful individual assessment of parameters is therefore recommended before use in practice.
    URI
    https://eresearch.qmu.ac.uk/handle/20.500.12289/10013
    Official URL
    http://dx.doi.org/10.21437/Interspeech.2019-2910
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