Acoustic investigation of speech pathologies based on the discriminative paraconsistent machine (DPM)

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.contributorIFSP - São Paulo Federal Institute-
Autor(es): dc.contributorUniversidade Estadual de Londrina (UEL)-
Autor(es): dc.contributorFATEC - São Paulo State Technology College-
Autor(es): dc.creatorFonseca, Everthon Silva [UNESP]-
Autor(es): dc.creatorGuido, Rodrigo Capobianco [UNESP]-
Autor(es): dc.creatorJunior, Sylvio Barbon-
Autor(es): dc.creatorDezani, Henrique-
Autor(es): dc.creatorGati, Rodrigo Rosseto-
Autor(es): dc.creatorMosconi Pereira, Denis César-
Data de aceite: dc.date.accessioned2022-02-22T00:32:49Z-
Data de disponibilização: dc.date.available2022-02-22T00:32:49Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2019-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.bspc.2019.101615-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/201174-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/201174-
Descrição: dc.descriptionBackground: Voice disorders are related to both modest and severe health problems, including discomfort, pain, difficulty speaking, dysphagia and also cancer. Widely adopted worldwide, the combined invasive and subjective diagnosis of voice disorders is troublesome and error-prone. Contrarily, acoustic-based digital assessment allows for a non-intrusive and objective examination, stimulating the applications of computer-based tools. Objective: Consequently, this work describes a novel algorithm to investigate speech pathologies from the sounds of sustained vowels, particularly exploring a potential gap: the classification of co-existent issues for which the major phonic symptom is the same, implying in similar inter-class features. Method: By using the concepts of signal energy (SE), zero-crossing rates (ZCRs) and signal entropy (SH), which provide a joint time-frequency-information map, the proposed approach classifies voice signals based on the discriminative paraconsistent machine (DPM), allowing for the application of paraconsistency to treat indefinitions and contradictions. Results: An accuracy level of 95% was obtained under a subset of voices from the Saarbrucken voice database (SVD), with just a modest training. In complement, the proposed approach offers wider possibilities in contrast to current state-of-the-art systems, allowing for the inputs to be mapped into the paraconsistent plane in such a way that intermediary states can be found. Conclusion: Different from current algorithms, our technique focuses on a particular problem in the field of speech pathology detection (SPD), not yet explored in detail, proposing a way to successfully solve it. Furthermore, the results we obtained stimulate broaden studies involving speech data inconsistencies whilst providing a valid contribution.-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionInstituto de Biociências Letras e Ciências Exatas Unesp - Univ Estadual Paulista (São Paulo State University), Rua Cristóvão Colombo 2265, Jd Nazareth, 15054-000-
Descrição: dc.descriptionIFSP - São Paulo Federal Institute Department of Industry and Automation-
Descrição: dc.descriptionUEL - Londrina State University Computer Science Department-
Descrição: dc.descriptionFATEC - São Paulo State Technology College-
Descrição: dc.descriptionInstituto de Biociências Letras e Ciências Exatas Unesp - Univ Estadual Paulista (São Paulo State University), Rua Cristóvão Colombo 2265, Jd Nazareth, 15054-000-
Idioma: dc.languageen-
Relação: dc.relationBiomedical Signal Processing and Control-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectCo-existent voice disorders-
Palavras-chave: dc.subjectDiscriminative paraconsistent machine (DPM)-
Palavras-chave: dc.subjectOverlapped inter-class features-
Palavras-chave: dc.subjectSignal energy (SE)-
Palavras-chave: dc.subjectSignal entropy (SH)-
Palavras-chave: dc.subjectZero-crossing rate (ZCR)-
Título: dc.titleAcoustic investigation of speech pathologies based on the discriminative paraconsistent machine (DPM)-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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