6 papers · 1 filter
Dynamic Real-Time Ambisonics Order Adaptation for Immersive Networked Music Performances
Paolo Ostan, Carlo Centofanti, Mirco Pezzoli +3
Advanced remote applications such as Networked Music Performance (NMP) require solutions to guarantee immersive real-world-like interaction among users. Therefore, the adoption of…
A Zero-Shot Physics-Informed Dictionary Learning Approach for Sound Field Reconstruction
Stefano Damiano, Federico Miotello, Mirco Pezzoli +4
Sound field reconstruction aims to estimate pressure fields in areas lacking direct measurements. Existing techniques often rely on strong assumptions or face challenges related to…
Data-Driven Room Acoustic Modeling Via Differentiable Feedback Delay Networks With Learnable Delay Lines
Alessandro Ilic Mezza, Riccardo Giampiccolo, Enzo De Sena +1
Over the past few decades, extensive research has been devoted to the design of artificial reverberation algorithms aimed at emulating the room acoustics of physical environments.…
The IEEE-IS2 2024 Music Packet Loss Concealment Challenge
Alessandro Ilic Mezza, Alberto Bernardini
We present the IEEE-IS2 2024 Music Packet Loss Concealment Challenge. We begin by detailing the challenge rules, followed by an overview of the provided baseline system, the blind…
A Physics-Informed Neural Network-Based Approach for the Spatial Upsampling of Spherical Microphone Arrays
Federico Miotello, Ferdinando Terminiello, Mirco Pezzoli +3
Spherical microphone arrays are convenient tools for capturing the spatial characteristics of a sound field. However, achieving superior spatial resolution requires arrays with num…
Toward Deep Drum Source Separation
Alessandro Ilic Mezza, Riccardo Giampiccolo, Alberto Bernardini +1
In the past, the field of drum source separation faced significant challenges due to limited data availability, hindering the adoption of cutting-edge deep learning methods that ha…