Javier Nistal

2 accepted papers

2026

DIFFUSION TIMBRE TRANSFER VIA MUTUAL INFORMATION GUIDED INPAINTING

Ching Ho Lee, Javier Nistal, Marco Pasini

ICASSP 2026poster

We study timbre transfer as an inference-time editing problem for music audio. Starting from a strong pre-trained latent diffusion model, we introduce a lightweight procedure that requires no additional training: (i) a dimension-wise noise injection that targets latent channels most informative of i…

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2025

Accompaniment Prompt Adherence: A measure for evaluating music accompaniment systems

Maarten Grachten, Javier Nistal

ICASSP 2025accepted

Generative systems of musical accompaniments are rapidly growing, yet there are no standardized metrics to evaluate how well generations align with the conditional audio prompt. We introduce a distribution-based measure called "Accompaniment Prompt Adherence" (APA), and validate it through objective…

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