138 citations · 302 across the 12 of their papers we have counts for
12 papers
CNN Models for Microphone Array Covariance Matrix Upsampling and Acoustic Imaging
Marianthi Adamopoulou, Parthasaarathy Sudarsanam, David Diaz-Guerra +5
Acoustic imaging visualization is a core methodology in acoustics, enabling spatial analysis of sound sources and acoustic scenes. However, limited sensor availability in practical…
Learning Input-Channel Permutation Equivariance for Multi-Channel Source Separation: Reducing Bleeding in Small Music Ensembles
Ruchi Pandey, Jaime Garcia-Martinez, Pablo Cabanas-Molero +5
Microphone bleed is a persistent challenge in small ensembles and orchestral recordings, where close microphones intended for individual instruments also capture leakage from nearb…
The Spheres Dataset: Multitrack Orchestral Recordings for Music Source Separation and Information Retrieval
Jaime Garcia-Martinez, David Diaz-Guerra, John Anderson +5
This paper introduces The Spheres dataset, multitrack orchestral recordings designed to advance machine learning research in music source separation and related MIR tasks within th…
Stereo Sound Event Localization and Detection with Onscreen/offscreen Classification
Kazuki Shimada, Archontis Politis, Iran R. Roman +10
This paper presents the objective, dataset, baseline, and metrics of Task 3 of the DCASE2025 Challenge on sound event localization and detection (SELD). In previous editions, the c…
Score-informed Music Source Separation: Improving Synthetic-to-real Generalization in Classical Music
Eetu Tunturi, David Diaz-Guerra, Archontis Politis +1
Music source separation is the task of separating a mixture of instruments into constituent tracks. Music source separation models are typically trained using only audio data, alth…
SynthSOD: Developing an Heterogeneous Dataset for Orchestra Music Source Separation
Jaime Garcia-Martinez, David Diaz-Guerra, Archontis Politis +3
Recent advancements in music source separation have significantly progressed, particularly in isolating vocals, drums, and bass elements from mixed tracks. These developments owe m…
Permutation Invariant Recurrent Neural Networks for Sound Source Tracking Applications
David Diaz-Guerra, Archontis Politis, Antonio Miguel +2
Many multi-source localization and tracking models based on neural networks use one or several recurrent layers at their final stages to track the movement of the sources. Conventi…
Position tracking of a varying number of sound sources with sliding permutation invariant training
David Diaz-Guerra, Archontis Politis, Tuomas Virtanen
Recent data- and learning-based sound source localization (SSL) methods have shown strong performance in challenging acoustic scenarios. However, little work has been done on adapt…
Direction of Arrival Estimation of Sound Sources Using Icosahedral CNNs
David Diaz-Guerra, Antonio Miguel, Jose R. Beltran
In this paper, we present a new model for Direction of Arrival (DOA) estimation of sound sources based on an Icosahedral Convolutional Neural Network (CNN) applied over SRP-PHAT po…
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…
Robust Sound Source Tracking Using SRP-PHAT and 3D Convolutional Neural Networks
David Diaz-Guerra, Antonio Miguel, Jose R. Beltran
In this paper, we present a new single sound source DOA estimation and tracking system based on the well-known SRP-PHAT algorithm and a three-dimensional Convolutional Neural Netwo…
gpuRIR: A Python Library for Room Impulse Response Simulation with GPU Acceleration
David Diaz-Guerra, Antonio Miguel, Jose R. Beltran
The Image Source Method (ISM) is one of the most employed techniques to calculate acoustic Room Impulse Responses (RIRs), however, its computational complexity grows fast with the…