7 citations · 17 across the 11 of their papers we have counts for
12 papers
On the Usefulness of Diffusion-Based Room Impulse Response Interpolation to Microphone Array Processing
Sagi Della Torre, Mirco Pezzoli, Fabio Antonacci +1
Room Impulse Responses estimation is a fundamental problem in spatial audio processing and speech enhancement. In this paper, we build upon our previously introduced diffusion-base…
Training-Free Multimodal Guidance for Video to Audio Generation
Eleonora Grassucci, Giuliano Galadini, Giordano Cicchetti +3
Video-to-audio (V2A) generation aims to synthesize realistic and semantically aligned audio from silent videos, with potential applications in video editing, Foley sound design, an…
AI-Assisted Music Production: A User Study on Text-to-Music Models
Francesca Ronchini, Luca Comanducci, Simone Marcucci +1
Text-to-music models have revolutionized the creative landscape, offering new possibilities for music creation. Yet their integration into musicians workflows remains underexplored…
Mitigating data replication in text-to-audio generative diffusion models through anti-memorization guidance
Francisco Messina, Francesca Ronchini, Luca Comanducci +2
A persistent challenge in generative audio models is data replication, where the model unintentionally generates parts of its training data during inference. In this work, we addre…
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…
Diffused Responsibility: Analyzing the Energy Consumption of Generative Text-to-Audio Diffusion Models
Riccardo Passoni, Francesca Ronchini, Luca Comanducci +2
Text-to-audio models have recently emerged as a powerful technology for generating sound from textual descriptions. However, their high computational demands raise concerns about e…
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…
Mind the Prompt: Prompting Strategies in Audio Generations for Improving Sound Classification
Francesca Ronchini, Ho-Hsiang Wu, Wei-Cheng Lin +1
This paper investigates the design of effective prompt strategies for generating realistic datasets using Text-To-Audio (TTA) models. We also analyze different techniques for effic…
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…
MambaFoley: Foley Sound Generation using Selective State-Space Models
Marco Furio Colombo, Francesca Ronchini, Luca Comanducci +1
Recent advancements in deep learning have led to widespread use of techniques for audio content generation, notably employing Denoising Diffusion Probabilistic Models (DDPM) across…
PAGURI: a user experience study of creative interaction with text-to-music models
Francesca Ronchini, Luca Comanducci, Gabriele Perego +1
In recent years, text-to-music models have been the biggest breakthrough in automatic music generation. While they are unquestionably a showcase of technological progress, it is no…