Search Results for author: Alberto Bernardini

Found 4 papers, 1 papers with code

Data-Driven Room Acoustic Modeling Via Differentiable Feedback Delay Networks With Learnable Delay Lines

no code implementations29 Mar 2024 Alessandro Ilic Mezza, Riccardo Giampiccolo, Enzo De Sena, Alberto Bernardini

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.

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

no code implementations21 Feb 2024 Federico Miotello, Paolo Ostan, Mirco Pezzoli, Luca Comanducci, Alberto Bernardini, Fabio Antonacci, Augusto Sarti

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 model a remote attendance teleconferencing scenario.

Toward Deep Drum Source Separation

1 code implementation15 Dec 2023 Alessandro Ilic Mezza, Riccardo Giampiccolo, Alberto Bernardini, Augusto Sarti

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 have found success in other related audio applications.

Reconstruction of Sound Field through Diffusion Models

no code implementations14 Dec 2023 Federico Miotello, Luca Comanducci, Mirco Pezzoli, Alberto Bernardini, Fabio Antonacci, Augusto Sarti

Reconstructing the sound field in a room is an important task for several applications, such as sound control and augmented (AR) or virtual reality (VR).

Denoising

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