9 citations · 17 across the 21 of their papers we have counts for
7 papers · 1 filter
End-to-End Historical Music Restoration in Latent Space
Steven Cho, Junghyun Koo, Raphael Lafargue +3
Historical music restoration (HMR) has almost exclusively focused on constrained problems such as Super-Resolution or the restoration of solo pieces, under-exploring the general ta…
Music Source Separation via Stem Discovery
V. Valtteri Kallinen, Eloi Moliner, Lauri Juvela +1
Music source separation (MSS) methods aim to extract stems from music mixtures, which is important, for example, in karaoke, music remixing, and pedagogical applications. While ear…
Estimation of Room Impulse Responses from Handclaps
Shih-Yu Lai, Kyung Yun Lee, Nils Meyer-Kahlen +3
Handclaps provide an equipment-free excitation for room acoustics, but their unknown and variable source waveform makes room impulse response (RIR) estimation challenging. In this…
Exact Factorisation and Fast Computation of Invertible Constant-Q Transforms
Facundo Franchino, Eloi Moliner, Vesa Välimäki
The constant-Q transform (CQT) represents audio on a logarithmic frequency axis. Its nonstationary Gabor formulation is exactly invertible, but the unequal numbers of time coeffici…
Ambisonics Encoding of Room Impulse Responses using a Device-Agnostic Diffusion Model
Eloi Moliner, Christoph Hold, Juan Azcarreta Ortiz +5
We address the problem of encoding room impulse responses (RIRs) into high-order Ambisonics (HOA) representations from arbitrary and potentially insufficient or incomplete micropho…
Music Restoration via Latent Operator Optimization and Diffusion Model Priors
Michal Švento, Eloi Moliner, Valtteri Kallinen +3
Music restoration seeks to recover a clean signal from an observed recording degraded by an unknown effect, distortion, or corruption. Existing systems often rely on paired trainin…
Automatic Audio Equalization with Semantic Embeddings
Eloi Moliner, Vesa Välimäki, Konstantinos Drossos +1
This paper presents a data-driven approach to automatic blind equalization of audio by predicting log-mel spectral features and deriving an inverse filter. The method uses a deep n…