12 citations · 30 across the 13 of their papers we have counts for
13 papers
Ontology-based Target Sound Extraction
Carlos Hernandez-Olivan, Marc Delcroix, Tsubasa Ochiai +2
Target sound extraction (TSE) aims to isolate a sound source of interest from a mixture, given a semantic query. Existing TSE systems are conditioned on fixed class representations…
Description and Discussion on DCASE 2026 Challenge Task 4: Spatial Semantic Segmentation of Sound Scenes
Binh Thien Nguyen, Masahiro Yasuda, Noboru Harada +8
This paper presents an overview of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2026 Challenge Task 4, Spatial Semantic Segmentation of Sound Scenes (S5).…
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…
VRDMG: Vocal Restoration via Diffusion Posterior Sampling with Multiple Guidance
Carlos Hernandez-Olivan, Koichi Saito, Naoki Murata +4
Restoring degraded music signals is essential to enhance audio quality for downstream music manipulation. Recent diffusion-based music restoration methods have demonstrated impress…
Symbolic Music Structure Analysis with Graph Representations and Changepoint Detection Methods
Carlos Hernandez-Olivan, Sonia Rubio Llamas, Jose R. Beltran
Music Structure Analysis is an open research task in Music Information Retrieval (MIR). In the past, there have been several works that attempt to segment music into the audio and…
A Survey on Artificial Intelligence for Music Generation: Agents, Domains and Perspectives
Carlos Hernandez-Olivan, Javier Hernandez-Olivan, Jose R. Beltran
Music is one of the Gardner's intelligences in his theory of multiple intelligences. How humans perceive and understand music is still being studied and is crucial to develop artif…
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…
Timbre Classification of Musical Instruments with a Deep Learning Multi-Head Attention-Based Model
Carlos Hernandez-Olivan, Jose R. Beltran
The aim of this work is to define a model based on deep learning that is able to identify different instrument timbres with as few parameters as possible. For this purpose, we have…
Music Boundary Detection using Convolutional Neural Networks: A comparative analysis of combined input features
Carlos Hernandez-Olivan, Jose R. Beltran, David Diaz-Guerra
The analysis of the structure of musical pieces is a task that remains a challenge for Artificial Intelligence, especially in the field of Deep Learning. It requires prior identifi…