8 citations · 20 across the 12 of their papers we have counts for
12 papers
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…
SCRAPL: Scattering Transform with Random Paths for Machine Learning
Christopher Mitcheltree, Vincent Lostanlen, Emmanouil Benetos +1
The Euclidean distance between wavelet scattering transform coefficients (known as paths) provides informative gradients for perceptual quality assessment of deep inverse problems…
Emergent musical properties of a transformer under contrastive self-supervised learning
Yuexuan Kong, Gabriel Meseguer-Brocal, Vincent Lostanlen +2
In music information retrieval (MIR), contrastive self-supervised learning for general-purpose representation models is effective for global tasks such as automatic tagging. Howeve…
S-KEY: Self-supervised Learning of Major and Minor Keys from Audio
Yuexuan Kong, Gabriel Meseguer-Brocal, Vincent Lostanlen +2
STONE, the current method in self-supervised learning for tonality estimation in music signals, cannot distinguish relative keys, such as C major versus A minor. In this article, w…
STONE: Self-supervised Tonality Estimator
Yuexuan Kong, Vincent Lostanlen, Gabriel Meseguer-Brocal +3
Although deep neural networks can estimate the key of a musical piece, their supervision incurs a massive annotation effort. Against this shortcoming, we present STONE, the first s…
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…
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…
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…
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…
Extended playing techniques: The next milestone in musical instrument recognition
Vincent Lostanlen, Joakim Andén, Mathieu Lagrange
The expressive variability in producing a musical note conveys information essential to the modeling of orchestration and style. As such, it plays a crucial role in computer-assist…