Encoder-decoder model with multi-task learning on a low-dimensional latent space improves dysarthria detection accuracy and enables generation of more fluent speech.
Re- constructing the voice of an individual following laryngectomy
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
Encoder-decoder model with multi-task learning on a low-dimensional latent space improves dysarthria detection accuracy and enables generation of more fluent speech.