3 papers
cs.LG2025
Conditional Diffusion as Latent Constraints for Controllable Symbolic Music Generation
Matteo Pettenó, Alessandro Ilic Mezza, Alberto Bernardini
Recent advances in latent diffusion models have demonstrated state-of-the-art performance in high-dimensional time-series data synthesis while providing flexible control through co…
cs.LG2025
On the Joint Minimization of Regularization Loss Functions in Deep Variational Bayesian Methods for Attribute-Controlled Symbolic Music Generation
Matteo Pettenó, Alessandro Ilic Mezza, Alberto Bernardini
Explicit latent variable models provide a flexible yet powerful framework for data synthesis, enabling controlled manipulation of generative factors. With latent variables drawn fr…
cs.SD2025
Attention-based Mixture of Experts for Robust Speech Deepfake Detection
Viola Negroni, Davide Salvi, Alessandro Ilic Mezza +2
AI-generated speech is becoming increasingly used in everyday life, powering virtual assistants, accessibility tools, and other applications. However, it is also being exploited fo…