Polyphonia improves zero-shot stem-specific timbre transfer in polyphonic music by 15.5% target alignment via acoustic-informed attention calibration that uses probabilistic priors to set coarse boundaries.
Mo \^ usai: Text-to-music generation with long-context latent diffusion
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AudioMoG is a mixture-of-guidance sampling technique that combines CFG and AG signals to outperform single-guidance baselines in text-to-audio generation at equivalent speed.
A data-free streaming consistency distillation framework enables single-step autoregressive generation from text-to-music models for real-time interactive use while preserving timbre and rhythm via latent, spectral, and temporal losses.
NeuroSonic introduces a conditional flow-matching framework that learns a deterministic transport from noise to speech conditioned on EEG, reporting up to 26.3% gains in perceptual quality over GAN, diffusion, and mean-flow baselines on cross-subject CineBrain and EAV evaluations.
citing papers explorer
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Polyphonia: Zero-Shot Timbre Transfer in Polyphonic Music with Acoustic-Informed Attention Calibration
Polyphonia improves zero-shot stem-specific timbre transfer in polyphonic music by 15.5% target alignment via acoustic-informed attention calibration that uses probabilistic priors to set coarse boundaries.
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AudioMoG: Guiding Audio Generation with Mixture-of-Guidance
AudioMoG is a mixture-of-guidance sampling technique that combines CFG and AG signals to outperform single-guidance baselines in text-to-audio generation at equivalent speed.
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Real-Time Interactive Music Generation via Data-Free Streaming Consistency Distillation
A data-free streaming consistency distillation framework enables single-step autoregressive generation from text-to-music models for real-time interactive use while preserving timbre and rhythm via latent, spectral, and temporal losses.
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NeuroSonic: Conditional Flow Matching for EEG-to-Speech Reconstruction
NeuroSonic introduces a conditional flow-matching framework that learns a deterministic transport from noise to speech conditioned on EEG, reporting up to 26.3% gains in perceptual quality over GAN, diffusion, and mean-flow baselines on cross-subject CineBrain and EAV evaluations.