8 citations · 18 across the 12 of their papers we have counts for
7 papers · 1 filter
Single-step Controllable Music Bandwidth Extension With Flow Matching
Carlos Hernandez-Olivan, Hendrik Vincent Koops, Hao Hao Tan +1
Audio restoration consists in inverting degradations of a digital audio signal to recover what would have been the pristine quality signal before the degradation occurred. This is…
SoundBeam meets M2D: Target Sound Extraction with Audio Foundation Model
Carlos Hernandez-Olivan, Marc Delcroix, Tsubasa Ochiai +4
Target sound extraction (TSE) consists of isolating a desired sound from a mixture of arbitrary sounds using clues to identify it. A TSE system requires solving two problems at onc…
Interaural time difference loss for binaural target sound extraction
Carlos Hernandez-Olivan, Marc Delcroix, Tsubasa Ochiai +3
Binaural target sound extraction (TSE) aims to extract a desired sound from a binaural mixture of arbitrary sounds while preserving the spatial cues of the desired sound. Indeed, f…
musicaiz: A Python Library for Symbolic Music Generation, Analysis and Visualization
Carlos Hernandez-Olivan, Jose R. Beltran
In this article, we present musicaiz, an object-oriented library for analyzing, generating and evaluating symbolic music. The submodules of the package allow the user to create sym…
Subjective Evaluation of Deep Learning Models for Symbolic Music Composition
Carlos Hernandez-Olivan, Jorge Abadias Puyuelo, Jose R. Beltran
Deep learning models are typically evaluated to measure and compare their performance on a given task. The metrics that are commonly used to evaluate these models are standard metr…
Music Composition with Deep Learning: A Review
Carlos Hernandez-Olivan, Jose R. Beltran
Generating a complex work of art such as a musical composition requires exhibiting true creativity that depends on a variety of factors that are related to the hierarchy of musical…