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Found 4 papers, 0 papers with code
On combining acoustic and modulation spectrograms in an attention LSTM-based system for speech intelligibility level classification
Speech intelligibility can be affected by multiple factors, such as noisy environments, channel distortions or physiological issues.
An Attention Long Short-Term Memory based system for automatic classification of speech intelligibility
Speech intelligibility can be degraded due to multiple factors, such as noisy environments, technical difficulties or biological conditions.
Automatic Detection of Depression in Speech Using Ensemble Convolutional Neural Networks
For the classification task itself, first, a more suitable architecture for this task, based on One-Dimensional Convolutional Neural Networks, is built.
Bayesian learning of feature spaces for multitasks problems
This paper introduces a novel approach for multi-task regression that connects Kernel Machines (KMs) and Extreme Learning Machines (ELMs) through the exploitation of the Random Fourier Features (RFFs) approximation of the RBF kernel.
