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Found 4 papers, 0 papers with code
A comparison of handcrafted, parameterized, and learnable features for speech separation
Among them, learnable features, which are trained with separation networks jointly in an end-to-end fashion, become a new trend of modern speech separation research, e. g. convolutional time domain audio separation network (Conv-Tasnet), while handcrafted and parameterized features are also shown competitive in very recent studies.
Sound
Hyperspectral Unmixing via Deep Autoencoder Networks for a Generalized Linear-Mixture/Nonlinear-Fluctuation Model
This paper presents an unsupervised nonlinear spectral unmixing method based on a deep autoencoder network that applies to a generalized linear-mixture/nonlinear fluctuation model, consisting of a linear mixture component and an additive nonlinear mixture component that depends on both endmembers and abundances.
Indoor Sound Source Localization with Probabilistic Neural Network
It is known that adverse environments such as high reverberation and low signal-to-noise ratio (SNR) pose a great challenge to indoor sound source localization.
Distributed Private Online Learning for Social Big Data Computing over Data Center Networks
An increasing number of people participate in social networks and massive online social data are obtained.
