Descripción
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Acoustic parameters are frequently used to assess the presence of pathologies in human voice. Many of them have demonstrated to be useful but in some cases its results could be optimized by selecting appropriate working margins. In this study two indices, CIL and RALA, obtained from Modulation Spectra are described and tuned using different frame lengths and frequency ranges to maximize AUC in normal to pathological voice detection. After the tuning process, AUC reaches 0.96 and 0.95 values for CIL and RALA respectively representing an improvement of 16 % and 12 % at each case respect to the typical tuning based only on frame length selection. | |
Internacional
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Si |
Nombre congreso
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Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) |
Tipo de participación
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960 |
Lugar del congreso
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Florencia - ITALIA |
Revisores
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Si |
ISBN o ISSN
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978-88-6655-792-0 |
DOI
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Fecha inicio congreso
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02/09/2015 |
Fecha fin congreso
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04/09/2015 |
Desde la página
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25 |
Hasta la página
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28 |
Título de las actas
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Models and Analysis of Vocal Emissions for Biomedical Applications (MAVEBA) - 9th International Workshop |