25 citations · 46 across the 19 of their papers we have counts for
7 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…
VR-PTOLEMAIC: A Virtual Environment for the Perceptual Testing of Spatial Audio Algorithms
Paolo Ostan, Francesca Del Gaudio, Federico Miotello +2
The perceptual evaluation of spatial audio algorithms is an important step in the development of immersive audio applications, as it ensures that synthesized sound fields meet qual…
Physics-Informed Transfer Learning for Data-Driven Sound Source Reconstruction in Near-Field Acoustic Holography
Xinmeng Luan, Mirco Pezzoli, Fabio Antonacci +1
We propose a transfer learning framework for sound source reconstruction in Near-field Acoustic Holography (NAH), which adapts a well-trained data-driven model from one type of sou…
Low-Rank Adaptation of Deep Prior Neural Networks For Room Impulse Response Reconstruction
Mirco Pezzoli, Federico Miotello, Shoichi Koyama +1
The Deep Prior framework has emerged as a powerful generative tool which can be used for reconstructing sound fields in an environment from few sparse pressure measurements. It emp…
Physics-Informed Neural Network-Driven Sparse Field Discretization Method for Near-Field Acoustic Holography
Xinmeng Luan, Mirco Pezzoli, Fabio Antonacci +1
We propose the Physics-Informed Neural Network-driven Sparse Field Discretization method (PINN-SFD), a novel self-supervised, physics-informed deep learning approach for addressing…
DiffusionRIR: Room Impulse Response Interpolation using Diffusion Models
Sagi Della Torre, Mirco Pezzoli, Fabio Antonacci +1
Room Impulse Responses (RIRs) characterize acoustic environments and are crucial in multiple audio signal processing tasks. High-quality RIR estimates drive applications such as vi…
Towards HRTF Personalization using Denoising Diffusion Models
Juan Camilo Albarracín Sánchez, Luca Comanducci, Mirco Pezzoli +1
Head-Related Transfer Functions (HRTFs) have fundamental applications for realistic rendering in immersive audio scenarios. However, they are strongly subject-dependent as they var…