Towards interpretable speech biomarkers: exploring MFCCs
Towards interpretable speech biomarkers: exploring MFCCs
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London: Nature Publishing Group UK
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English
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London: Nature Publishing Group UK
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While speech biomarkers of disease have attracted increased interest in recent years, a challenge is that features derived from signal processing or machine learning approaches may lack clinical interpretability. As an example, Mel frequency cepstral coefficients (MFCCs) have been identified in several studies as a useful marker of disease, but are...
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Towards interpretable speech biomarkers: exploring MFCCs
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TN_cdi_doaj_primary_oai_doaj_org_article_e0ea7c4330da4036a2bfa9add0fd51ff
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e0ea7c4330da4036a2bfa9add0fd51ff
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ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-023-49352-2
