Automatic cross‐ and multi‐lingual recognition of dysphonia by ensemble classification using deep speaker embedding models
Dosti Aziz,
Dávid Sztahó
Abstract:Machine Learning (ML) algorithms have demonstrated remarkable performance in dysphonia detection using speech samples. However, their efficacy often diminishes when tested on languages different from the training data, raising questions about their suitability in clinical settings. This study aims to develop a robust method for cross‐ and multi‐lingual dysphonia detection that overcomes the limitation of language dependency in existing ML methods. We propose an innovative approach that leverages speech embeddi… Show more
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