2021
INTERSPEECH
INTERSPEECH 2021
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling
Abstract
In this work, we introduce NU-Wave, the first neural audio upsampling model to produce waveforms of sampling rate 48kHz from coarse 16kHz or 24kHz inputs, while prior works could generate only up to 16kHz. NU-Wave is the first diffusion probabilistic model for audio super-resolution which is engineered based on neural vocoders. NU-Wave generates high-quality audio that achieves high performance in terms of signal-to-noise ratio (SNR), log-spectral distance (LSD), and accuracy of the ABX test. In all cases, NU-Wave outperforms the baseline models despite the substantially smaller model capacity (3.0M parameters) than baselines (5.4–21%). The audio samples of our model are publicly available, and the code will be made available soon.
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Interdisciplinary Bridge
— Computer Vision and Machine Learning
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Keyword Pioneer
— log-spectral distance
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Hot Topic Early Bird
— diffusion probabilistic model
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio