6 citations · 12 across the 6 of their papers we have counts for
6 papers · 1 filter
Musical Metamerism with Time--Frequency Scattering
Vincent Lostanlen, Han Han
The concept of metamerism originates from colorimetry, where it describes a sensation of visual similarity between two colored lights despite significant differences in spectral co…
Learning to Solve Inverse Problems for Perceptual Sound Matching
Han Han, Vincent Lostanlen, Mathieu Lagrange
Perceptual sound matching (PSM) aims to find the input parameters to a synthesizer so as to best imitate an audio target. Deep learning for PSM optimizes a neural network to analyz…
Fitting Auditory Filterbanks with Multiresolution Neural Networks
Vincent Lostanlen, Daniel Haider, Han Han +3
Waveform-based deep learning faces a dilemma between nonparametric and parametric approaches. On one hand, convolutional neural networks (convnets) may approximate any linear time-…
Mesostructures: Beyond Spectrogram Loss in Differentiable Time-Frequency Analysis
Cyrus Vahidi, Han Han, Changhong Wang +3
Computer musicians refer to mesostructures as the intermediate levels of articulation between the microstructure of waveshapes and the macrostructure of musical forms. Examples of…
Perceptual-Neural-Physical Sound Matching
Han Han, Vincent Lostanlen, Mathieu Lagrange
Sound matching algorithms seek to approximate a target waveform by parametric audio synthesis. Deep neural networks have achieved promising results in matching sustained harmonic t…
wav2shape: Hearing the Shape of a Drum Machine
Han Han, Vincent Lostanlen
Disentangling and recovering physical attributes, such as shape and material, from a few waveform examples is a challenging inverse problem in audio signal processing, with numerou…