Abstract
This work aims to detect vocal disorders related to vocal nodule and Reinke’s edema through non-linear features. The features are computed from the fullband and, by means of the wavelet transform, from sub-bands of sustained vowel. The wavelet that maximizes the individual discriminating capacity of the features is sought. Two sub-band parameter selections are performed. The fullband and sub-band parameters, and the selected sets are applied to several classifiers with leave-one-out cross-validation. Classification accuracies of up to 86.2% are obtained without parameter selection while accuracies of up to 100% are achieved with selected parameters.
Original language | Portuguese |
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Title of host publication | XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais |
Publisher | Sociedade Brasileira de Telecomunicações |
Pages | 1-5 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 26 Sept 2021 |
Event | XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais - Fortaleza, Brazil Duration: 26 Sept 2021 → 29 Sept 2021 |
Conference
Conference | XXXIX Simpósio Brasileiro de Telecomunicações e Processamento de Sinais |
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Abbreviated title | SBrT2021 |
Country/Territory | Brazil |
City | Fortaleza |
Period | 26/09/21 → 29/09/21 |
Keywords
- Vocal nodule
- Reinke’s edema
- Nonlinear features
- Wavelet
- Classification