22 citations · 43 across the 10 of their papers we have counts for
10 papers
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-…
Foley Sound Synthesis at the DCASE 2023 Challenge
Keunwoo Choi, Jaekwon Im, Laurie Heller +5
The addition of Foley sound effects during post-production is a common technique used to enhance the perceived acoustic properties of multimedia content. Traditionally, Foley sound…
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…
Differentiable Time-Frequency Scattering on GPU
John Muradeli, Cyrus Vahidi, Changhong Wang +4
Joint time-frequency scattering (JTFS) is a convolutional operator in the time-frequency domain which extracts spectrotemporal modulations at various rates and scales. It offers an…
Time-Frequency Scattering Accurately Models Auditory Similarities Between Instrumental Playing Techniques
Vincent Lostanlen, Christian El-Hajj, Mathias Rossignol +3
Instrumental playing techniques such as vibratos, glissandos, and trills often denote musical expressivity, both in classical and folk contexts. However, most existing approaches t…