3 citations · 3 across the 4 of their papers we have counts for
4 papers
Hyperbolic Audio Source Separation
Darius Petermann, Gordon Wichern, Aswin Subramanian +1
We introduce a framework for audio source separation using embeddings on a hyperbolic manifold that compactly represent the hierarchical relationship between sound sources and time…
SpaIn-Net: Spatially-Informed Stereophonic Music Source Separation
Darius Petermann, Minje Kim
With the recent advancements of data driven approaches using deep neural networks, music source separation has been formulated as an instrument-specific supervised problem. While e…
HARP-Net: Hyper-Autoencoded Reconstruction Propagation for Scalable Neural Audio Coding
Darius Petermann, Seungkwon Beack, Minje Kim
An autoencoder-based codec employs quantization to turn its bottleneck layer activation into bitstrings, a process that hinders information flow between the encoder and decoder par…
Deep Learning Based Source Separation Applied To Choir Ensembles
Darius Petermann, Pritish Chandna, Helena Cuesta +2
Choral singing is a widely practiced form of ensemble singing wherein a group of people sing simultaneously in polyphonic harmony. The most commonly practiced setting for choir ens…