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20232026
most citedPhysics-Informed Transfer Learning for Data-Driven Sound Source Reconstruction in Near-Field Acoustic Holography

1 citations · 2 across the 10 of their papers we have counts for

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Showing 2024 · eess.ASShow all

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eess.AS2024★ 1 cited

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…

eess.AS2024

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…

eess.AS2024

Interpreting End-to-End Deep Learning Models for Speech Source Localization Using Layer-wise Relevance Propagation

Luca Comanducci, Fabio Antonacci, Augusto Sarti

Deep learning models are widely applied in the signal processing community, yet their inner working procedure is often treated as a black box. In this paper, we investigate the use…

eess.AS2024

Physics-Informed Neural Network for Volumetric Sound field Reconstruction of Speech Signals

Marco Olivieri, Xenofon Karakonstantis, Mirco Pezzoli +3

Recent developments in acoustic signal processing have seen the integration of deep learning methodologies, alongside the continued prominence of classical wave expansion-based app…

eess.AS2024

HOMULA-RIR: A Room Impulse Response Dataset for Teleconferencing and Spatial Audio Applications Acquired Through Higher-Order Microphones and Uniform Linear Microphone Arrays

Federico Miotello, Paolo Ostan, Mirco Pezzoli +4

In this paper, we present HOMULA-RIR, a dataset of room impulse responses (RIRs) acquired using both higher-order microphones (HOMs) and a uniform linear array (ULA), in order to m…

eess.AS2024

Room Transfer Function Reconstruction Using Complex-valued Neural Networks and Irregularly Distributed Microphones

Francesca Ronchini, Luca Comanducci, Mirco Pezzoli +2

Reconstructing the room transfer functions needed to calculate the complex sound field in a room has several important real-world applications. However, an unpractical number of mi…