7 papers · 1 filter
PHALAR: Phasors for Learned Musical Audio Representations
Davide Marincione, Michele Mancusi, Giorgio Strano +4
Stem retrieval, the task of matching missing stems to a given audio submix, is a key challenge currently limited by models that discard temporal information. We introduce PHALAR, a…
EuleroDec: A Complex-Valued RVQ-VAE for Efficient and Robust Audio Coding
Luca Cerovaz, Michele Mancusi, Emanuele RodolÃ
Audio codecs power discrete music generative modelling, music streaming and immersive media by shrinking PCM audio to bandwidth-friendly bit-rates. Recent works have gravitated tow…
LoopGen: Training-Free Loopable Music Generation
Davide Marincione, Giorgio Strano, Donato Crisostomi +2
Loops--short audio segments designed for seamless repetition--are central to many music genres, particularly those rooted in dance and electronic styles. However, current generativ…
STAGE: Stemmed Accompaniment Generation through Prefix-Based Conditioning
Giorgio Strano, Chiara Ballanti, Donato Crisostomi +3
Recent advances in generative models have made it possible to create high-quality, coherent music, with some systems delivering production-level output. Yet, most existing models f…
Activation Patching for Interpretable Steering in Music Generation
Simone Facchiano, Giorgio Strano, Donato Crisostomi +4
Understanding how large audio models represent music, and using that understanding to steer generation, is both challenging and underexplored. Inspired by mechanistic interpretabil…
Naturalistic Music Decoding from EEG Data via Latent Diffusion Models
Emilian Postolache, Natalia Polouliakh, Hiroaki Kitano +4
In this article, we explore the potential of using latent diffusion models, a family of powerful generative models, for the task of reconstructing naturalistic music from electroen…