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Found 4 papers, 4 papers with code
Points2Sound: From mono to binaural audio using 3D point cloud scenes
We propose Points2Sound, a multi-modal deep learning model which generates a binaural version from mono audio using 3D point cloud scenes.
Music source separation conditioned on 3D point clouds
This paper proposes a multi-modal deep learning model to perform music source separation conditioned on 3D point clouds of music performance recordings.
Sound field reconstruction in rooms: inpainting meets super-resolution
In particular, the presented approach uses a limited number of arbitrary discrete measurements of the magnitude of the sound field pressure in order to extrapolate this field to a higher-resolution grid of discrete points in space with a low computational complexity.
End-to-end music source separation: is it possible in the waveform domain?
Most of the currently successful source separation techniques use the magnitude spectrogram as input, and are therefore by default omitting part of the signal: the phase.
Ranked #25 on
Music Source Separation
on MUSDB18
