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arxiv.org arXiv
arxiv.org › abs › 2305.15266v3
Audio inpainting aims to reconstruct missing segments in corrupted recordings. Most of existing methods produce plausible reconstructions when the gap lengths are short, but struggle to reconstruct ga...
arxiv.org arXiv
arxiv.org › abs › 1908.02590v3
Variational auto-encoders (VAEs) are deep generative latent variable models that can be used for learning the distribution of complex data. VAEs have been successfully used to learn a probabilistic pr...
arxiv.org arXiv
arxiv.org › abs › 1905.06148v2
Audio processors whose parameters are modified periodically over time are often referred as time-varying or modulation based audio effects. Most existing methods for modeling these type of effect unit...
arxiv.org arXiv
arxiv.org › abs › 2411.18222v1
Efficient audio quality assessment is vital for streamlining audio codec development. Objective assessment tools have been developed over time to algorithmically predict quality ratings from subjectiv...
arxiv.org arXiv
arxiv.org › abs › 2505.20166v3
Audio-aware large language models (ALLMs) have recently made great strides in understanding and processing audio inputs. These models are typically adapted from text-based large language models (LLMs)...
arxiv.org arXiv
arxiv.org › abs › 2105.01531v2
Influenced by the field of Computer Vision, Generative Adversarial Networks (GANs) are often adopted for the audio domain using fixed-size two-dimensional spectrogram representations as the "image dat...
arxiv.org arXiv
arxiv.org › abs › gr-qc › 9810059v1
The space-time foliation Sigma compatible with the gravitational field g on a 4-manifold M determines a fibration pi of M, pi : M -> N is a surjective submersion over the 1-dimensional leaves space N....
arxiv.org arXiv
arxiv.org › abs › 2501.04116v3
Recent advances in deep neural networks (DNNs) have significantly improved various audio processing applications, including speech enhancement, synthesis, and hearing-aid algorithms. DNN-based closed-...
arxiv.org arXiv
arxiv.org › abs › 2311.08396v1
Zero-shot audio captioning aims at automatically generating descriptive textual captions for audio content without prior training for this task. Different from speech recognition which translates audi...
arxiv.org arXiv
arxiv.org › abs › 2102.01243v3
Audio tagging is an active research area and has a wide range of applications. Since the release of AudioSet, great progress has been made in advancing model performance, which mostly comes from the d...