Publications (25)
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…
Detection of Deepfake Environmental Audio
Hafsa Ouajdi, Oussama Hadder, Modan Tailleur +2
With the ever-rising quality of deep generative models, it is increasingly important to be able to discern whether the audio data at hand have been recorded or synthesized. Althoug…
Challenge on Sound Scene Synthesis: Evaluating Text-to-Audio Generation
Junwon Lee, Modan Tailleur, Laurie M. Heller +5
Despite significant advancements in neural text-to-audio generation, challenges persist in controllability and evaluation. This paper addresses these issues through the Sound Scene…
Efficient bandwidth extension of musical signals using a differentiable harmonic plus noise model
Pierre-Amaury Grumiaux, Mathieu Lagrange
The task of bandwidth extension addresses the generation of missing high frequencies of audio signals based on knowledge of the low-frequency part of the sound. This task applies t…
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…