Elastic Time adds a learned latent predictor to enable dynamic frame rates in fixed-rate neural audio autoencoders, allowing skipped frames to be reconstructed and improving efficiency-quality tradeoffs at deployment time.
Moisesdb: A dataset for source separation beyond 4-stems.arXiv preprint arXiv:2307.15913
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MERIT trains disentangled heads for melody, rhythm, and timbre via conditional audio generation and stem separation, with evaluations showing each head responds strongly to its target dimension and near chance on others across synthetic and real audio.
A cold diffusion model with direct and delta-normalized reverse processes, using UNet and transformer backbones, outperforms diffusion baselines for dereverberating acoustic and electronic drum stems on in-domain and out-of-domain tests.
citing papers explorer
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Elastic Time: Dynamic Frame Rate Bottlenecks for Neural Audio Coding
Elastic Time adds a learned latent predictor to enable dynamic frame rates in fixed-rate neural audio autoencoders, allowing skipped frames to be reconstructed and improving efficiency-quality tradeoffs at deployment time.
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MERIT: Learning Disentangled Music Representations for Audio Similarity
MERIT trains disentangled heads for melody, rhythm, and timbre via conditional audio generation and stem separation, with evaluations showing each head responds strongly to its target dimension and near chance on others across synthetic and real audio.
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A Cold Diffusion Approach for Percussive Dereverberation
A cold diffusion model with direct and delta-normalized reverse processes, using UNet and transformer backbones, outperforms diffusion baselines for dereverberating acoustic and electronic drum stems on in-domain and out-of-domain tests.
- A Survey of Advancing Audio Super-Resolution and Bandwidth Extension from Discriminative to Generative Models