Telephony-based voice pathology assessment using automated speech analysis.
IEEE Trans Biomed Eng
; 53(3): 468-77, 2006 Mar.
Article
em En
| MEDLINE
| ID: mdl-16532773
ABSTRACT
A system for remotely detecting vocal fold pathologies using telephone-quality speech is presented. The system uses a linear classifier, processing measurements of pitch perturbation, amplitude perturbation and harmonic-to-noise ratio derived from digitized speech recordings. Voice recordings from the Disordered Voice Database Model 4337 system were used to develop and validate the system. Results show that while a sustained phonation, recorded in a controlled environment, can be classified as normal or pathologic with accuracy of 89.1%, telephone-quality speech can be classified as normal or pathologic with an accuracy of 74.2%, using the same scheme. Amplitude perturbation features prove most robust for telephone-quality speech. The pathologic recordings were then subcategorized into four groups, comprising normal, neuromuscular pathologic, physical pathologic and mixed (neuromuscular with physical) pathologic. A separate classifier was developed for classifying the normal group from each pathologic subcategory. Results show that neuromuscular disorders could be detected remotely with an accuracy of 87%, physical abnormalities with an accuracy of 78% and mixed pathology voice with an accuracy of 61%. This study highlights the real possibility for remote detection and diagnosis of voice pathology.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Espectrografia do Som
/
Distúrbios da Fala
/
Medida da Produção da Fala
/
Telefone
/
Inteligência Artificial
/
Diagnóstico por Computador
/
Telemedicina
Tipo de estudo:
Diagnostic_studies
/
Evaluation_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
IEEE Trans Biomed Eng
Ano de publicação:
2006
Tipo de documento:
Article
País de afiliação:
Irlanda