<ul><li>Amyotrophic Lateral Sclerosis (ALS) patients often suffer from dysarthria, a decline in speech intelligibility.</li><li>Existing studies rely on feature extraction and customized convolutional neural networks to recognize dysarthria in ALS patients.</li><li>This research introduces the use of hypernetworks to recognize dysarthria in ALS patients by generating weights for a target network.</li><li>Experimental results on the VOC-ALS dataset show that the proposed approach outperforms strong baselines, achieving up to 82.66% accuracy.</li></ul>

Recognition of Dysarthria in Amyotrophic Lateral Sclerosis patients using Hypernetworks

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