9 citations · 28 across the 13 of their papers we have counts for
12 papers · 1 filter
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…
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…
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…
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…
Synthetic training set generation using text-to-audio models for environmental sound classification
Francesca Ronchini, Luca Comanducci, Fabio Antonacci
In recent years, text-to-audio models have revolutionized the field of automatic audio generation. This paper investigates their application in generating synthetic datasets for tr…
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…
Performance and energy balance: a comprehensive study of state-of-the-art sound event detection systems
Francesca Ronchini, Romain Serizel
In recent years, deep learning systems have shown a concerning trend toward increased complexity and higher energy consumption. As researchers in this domain and organizers of one…
Description and analysis of novelties introduced in DCASE Task 4 2022 on the baseline system
Francesca Ronchini, Samuele Cornell, Romain Serizel +3
The aim of the Detection and Classification of Acoustic Scenes and Events Challenge Task 4 is to evaluate systems for the detection of sound events in domestic environments using a…
A benchmark of state-of-the-art sound event detection systems evaluated on synthetic soundscapes
Francesca Ronchini, Romain Serizel
This paper proposes a benchmark of submissions to Detection and Classification Acoustic Scene and Events 2021 Challenge (DCASE) Task 4 representing a sampling of the state-of-the-a…
The impact of non-target events in synthetic soundscapes for sound event detection
Francesca Ronchini, Romain Serizel, Nicolas Turpault +1
Detection and Classification Acoustic Scene and Events Challenge 2021 Task 4 uses a heterogeneous dataset that includes both recorded and synthetic soundscapes. Until recently only…
Sound event localization and detection based on crnn using rectangular filters and channel rotation data augmentation
Francesca Ronchini, Daniel Arteaga, Andrés Pérez-López
Sound Event Localization and Detection refers to the problem of identifying the presence of independent or temporally-overlapped sound sources, correctly identifying to which sound…