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Luca Comanducci

5 accepted papers

2025

MambaFoley: Foley Sound Generation using Selective State-Space Models

ICASSP 2025accepted

Recent advancements in deep learning have led to widespread use of techniques for audio content generation, notably employing Denoising Diffusion Probabilistic Models (DDPM) across various tasks. Among these, Foley Sound Synthesis is of particular interest for its role in applications for the creati…

Cited by 0SourceScholar
2025

Towards HRTF Personalization using Denoising Diffusion Models

ICASSP 2025accepted

Head-Related Transfer Functions (HRTFs) have fundamental applications for realistic rendering in immersive audio scenarios. However, they are strongly subject-dependent as they vary considerably depending on the shape of the ears, head and torso. Thus, personalization procedures are required for acc…

Cited by 0SourceScholar
2024

Reconstruction of Sound Field Through Diffusion Models

ICASSP 2024accepted

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). In this paper, we propose a data-driven generative model for reconstructing the magnitude of acoustic fields in rooms with a focus on the modal fr…

Cited by 0SourceScholar
2023

Real-Time Multichannel Speech Separation and Enhancement Using a Beamspace-Domain-Based Lightweight CNN

ICASSP 2023accepted

The problems of speech separation and enhancement concern the extraction of the speech emitted by a target speaker when placed in a scenario where multiple interfering speakers or noise are present, respectively. A plethora of practical applications such as home assistants and teleconferencing requi…

Cited by 0SourceScholar
2020

Time Difference of Arrival Estimation from Frequency-Sliding Generalized Cross-Correlations Using Convolutional Neural Networks

ICASSP 2020accepted

The interest in deep learning methods for solving traditional signal processing tasks has been steadily growing in the last years. Time delay estimation (TDE) in adverse scenarios is a challenging problem, where classical approaches based on generalized cross-correlations (GCCs) have been widely use…

Cited by 0SourceScholar