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…
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…
Sound Event Detection in Synthetic Audio: Analysis of the DCASE 2016 Task Results
Grégoire Lafay, Emmanouil Benetos, Mathieu Lagrange
As part of the 2016 public evaluation challenge on Detection and Classification of Acoustic Scenes and Events (DCASE 2016), the second task focused on evaluating sound event detect…
An evaluation framework for event detection using a morphological model of acoustic scenes
Mathieu Lagrange, Grégoire Lafay, Mathias Rossignol +2
This paper introduces a model of environmental acoustic scenes which adopts a morphological approach by ab-stracting temporal structures of acoustic scenes. To demonstrate its pote…
The bag-of-frames approach: a not so sufficient model for urban soundscapes
Mathieu Lagrange, Grégoire Lafay, Boris Defreville +1
The "bag-of-frames" approach (BOF), which encodes audio signals as the long-term statistical distribution of short-term spectral features, is commonly regarded as an effective and…