5 papers
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…
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…
An incremental algorithm based on multichannel non-negative matrix partial co-factorization for ambient denoising in auscultation
Juan De La Torre Cruz, Francisco Jesus Canadas Quesada, Damian Martinez-Munoz +3
The aim of this study is to implement a method to remove ambient noise in biomedical sounds captured in auscultation. We propose an incremental approach based on multichannel non-n…
Improving snore detection under limited dataset through harmonic/percussive source separation and convolutional neural networks
F. D. Gonzalez-Martinez, J. J. Carabias-Orti, F. J. Canadas-Quesada +3
Snoring, an acoustic biomarker commonly observed in individuals with Obstructive Sleep Apnoea Syndrome (OSAS), holds significant potential for diagnosing and monitoring this recogn…