Automatic Voice Disorder Detection using Self-Supervised Representations

Many speech features and models, including Deep Neural Networks (DNN), are used for classification tasks between healthy and pathological speech with the Saarbruecken Voice Database (SVD). However, accuracy values of 80.71% for phrases or 82.8% for vowels /aiu/ are the highest reported for audio sam...

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Veröffentlicht in:	IEEE access 2023-01, Vol.11, p.1-1
Hauptverfasser:	Ribas, Dayana, Pastor, Miguel A., Miguel, Antonio, Martinez, David, Ortega, Alfonso, Lleida, Eduardo
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Advanced Voice Function Assessment Database Artificial neural networks Availability class token Classification Deep learning Deep Neural Networks Domains Machine learning Neural networks pathological speech Pathology Representations Saarbruecken Voice Database self-supervised Self-supervised learning Speech Training Training data transformer Transformers Voice disorder Voice recognition
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