A2SB: Audio-to-Audio Schrodinger Bridges
원문 초록
Audio in the real world may be perturbed due to numerous factors, causing the audio quality to be degraded. The following work presents an audio restoration model tailored for high-res music at 44.1kHz. Our model, Audio-to-Audio Schrodinger Bridges (A2SB), is capable of both bandwidth extension (predicting high-frequency components) and inpainting (re-generating missing segments). Critically, A2SB is end-to-end without need of a vocoder to predict waveform outputs, able to restore hour-long audio inputs, and trained on permissively licensed music data. A2SB is capable of achieving state-of-the-art bandwidth extension and inpainting quality on several out-of-distribution music test sets. Our demo website is https: //research.nvidia.com/labs/adlr/A2SB/.
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Generative Speech Foundation Model Pretraining for High-Quality Speech Extraction and Restoration
Vibravox: A Dataset of French Speech Captured with Body-conduction Audio Sensors
Multi-Stage Speech Bandwidth Extension with Flexible Sampling Rate Control
A Diffusion-Based Generative Equalizer for Music Restoration
Towards High-Quality and Efficient Speech Bandwidth Extension with Parallel Amplitude and Phase Prediction
Configurable EBEN: Extreme Bandwidth Extension Network to enhance body-conducted speech capture
토론
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