Papers Audio Super-Resolution
“Audio Super-Resolution” 태그가 달린 논문 28편 · 필터 해제
Self-Attention for Audio Super-Resolution
Convolutions operate only locally, thus failing to model global interactions. Self-attention is, however, able to learn representations that capture long-range dependencies in sequences. We propose a network architecture…
Audio Super-ResolutionSuper-ResolutionNU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling
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…
Audio Super-ResolutionSuper-ResolutionOn Filter Generalization for Music Bandwidth Extension Using Deep Neural Networks
In this paper, we address a sub-topic of the broad domain of audio enhancement, namely musical audio bandwidth extension. We formulate the bandwidth extension problem using deep neural networks, where a band-limited sign…
Audio Super-ResolutionBandwidth ExtensionData AugmentationTemporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations.
Learning representations that accurately capture long-range dependencies in sequential inputs --- including text, audio, and genomic data --- is a key problem in deep learning. Feed-forward convolutional models capture o…
Audio Super-ResolutionSuper-Resolutiontext-classificationText ClassificationLearning to Have an Ear for Face Super-Resolution
We propose a novel method to use both audio and a low-resolution image to perform extreme face super-resolution (a 16x increase of the input size). When the resolution of the input image is very low (e.g., 8x8 pixels), t…
Audio Super-ResolutionFace ReconstructionImage ReconstructionSuper-ResolutionTemporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations
Learning representations that accurately capture long-range dependencies in sequential inputs -- including text, audio, and genomic data -- is a key problem in deep learning. Feed-forward convolutional models capture onl…
Audio Super-ResolutionSuper-Resolutiontext-classificationText ClassificationAdversarial Audio Super-Resolution with Unsupervised Feature Losses
Neural network-based methods have recently demonstrated state-of-the-art results on image synthesis and super-resolution tasks, in particular by using variants of generative adversarial networks (GANs) with supervised fe…
Audio Super-ResolutionImage GenerationSuper-ResolutionAudio Super Resolution using Neural Networks
We introduce a new audio processing technique that increases the sampling rate of signals such as speech or music using deep convolutional neural networks. Our model is trained on pairs of low and high-quality audio exam…
Audio GenerationAudio Super-ResolutionSuper-Resolutiontext-to-speech+1