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Automatic dysarthric speech detection exploiting pairwise distance-based convolutional neural networks
Automatic dysarthric speech detection can provide reliable and cost-effective computer-aided tools to assist the clinical diagnosis and management of dysarthria.
Multi-task single channel speech enhancement using speech presence probability as a secondary task training target
Simulation results show that the dereverberation and noise reduction performance of a single-task DNN trained to directly estimate the Wiener gain is higher than the performance of single-task DNNs trained to estimate the desired signal magnitude, the interference power spectral density, or the signal-to-interference ratio.
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