collaborators

7 papers

eess.AS2026

Physics-Guided Variational Model for Unsupervised Sound Source Tracking

Luan Vinícius Fiorio, Ivana Nikoloska, Bruno Defraene +3

Sound source tracking is commonly performed using classical array-processing algorithms, while machine-learning approaches typically rely on precise source position labels that are…

eess.AS2026

Clustering of Acoustic Environments with Variational Autoencoders for Hearing Devices

Luan Vinícius Fiorio, Ivana Nikoloska, Wim van Houtum +1

Traditional acoustic environment classification relies on: i) classical signal processing algorithms, which are unable to extract meaningful representations of high-dimensional dat…

eess.AS2026

Categorical Unsupervised Variational Acoustic Clustering

Luan Vinícius Fiorio, Ivana Nikoloska, Ronald M. Aarts

We propose a categorical approach for unsupervised variational acoustic clustering of audio data in the time-frequency domain. The consideration of a categorical distribution enfor…

eess.AS2026

Unsupervised Variational Acoustic Clustering

Luan Vinícius Fiorio, Bruno Defraene, Johan David +3

We propose an unsupervised variational acoustic clustering model for clustering audio data in the time-frequency domain. The model leverages variational inference, extended to an a…

eess.AS2025

Hybrid Real- and Complex-Valued Neural Network Architecture for Speech Enhancement

Luan Vinícius Fiorio, Luan Vinícius Fiorio, Alex Young +1

This paper investigates hybrid real- and complex-valued neural networks for monaural speech enhancement. While complex-valued models can process time-frequency representations nati…

cs.LG2025

Hybrid Real- and Complex-valued Neural Network Architecture

Alex Young, Luan Vinícius Fiorio, Bo Yang +3

We propose a \emph{hybrid} real- and complex-valued \emph{neural network} (HNN) architecture, designed to combine the computational efficiency of real-valued processing with the ab…