Bandwidth Extension

15 papers with code • 1 benchmarks • 1 datasets

Bandwidth extension is the task of expanding the bandwidth of a signal in a way that approximates the original or desired higher bandwidth signal.


Most implemented papers

On Filter Generalization for Music Bandwidth Extension Using Deep Neural Networks

serkansulun/deep-music-enhancer 14 Nov 2020

In this paper, we address a sub-topic of the broad domain of audio enhancement, namely musical audio bandwidth extension.

HiFi++: a Unified Framework for Bandwidth Extension and Speech Enhancement

andreevp/wvmos 24 Mar 2022

Generative adversarial networks have recently demonstrated outstanding performance in neural vocoding outperforming best autoregressive and flow-based models.

Super-Resolution with Deep Convolutional Sufficient Statistics

Adk2001tech/GAN-Image-Super-Resolution 18 Nov 2015

Inverse problems in image and audio, and super-resolution in particular, can be seen as high-dimensional structured prediction problems, where the goal is to characterize the conditional distribution of a high-resolution output given its low-resolution corrupted observation.

Wavenet based low rate speech coding

google/lyra 1 Dec 2017

Traditional parametric coding of speech facilitates low rate but provides poor reconstruction quality because of the inadequacy of the model used.

TUNet: A Block-online Bandwidth Extension Model based on Transformers and Self-supervised Pretraining

nxtproduct/tunet 26 Oct 2021

We introduce a block-online variant of the temporal feature-wise linear modulation (TFiLM) model to achieve bandwidth extension.

Neural Vocoder is All You Need for Speech Super-resolution

haoheliu/ssr_eval 28 Mar 2022

In this paper, we propose a neural vocoder based speech super-resolution method (NVSR) that can handle a variety of input resolution and upsampling ratios.

BEHM-GAN: Bandwidth Extension of Historical Music using Generative Adversarial Networks

eloimoliner/bwe_historical_recordings 13 Apr 2022

Audio bandwidth extension aims to expand the spectrum of narrow-band audio signals.

EBEN: Extreme bandwidth extension network applied to speech signals captured with noise-resilient body-conduction microphones

jhauret/eben 25 Oct 2022

In this paper, we present Extreme Bandwidth Extension Network (EBEN), a Generative Adversarial network (GAN) that enhances audio measured with body-conduction microphones.

Solving Audio Inverse Problems with a Diffusion Model

eloimoliner/cqtdiff 27 Oct 2022

This paper presents CQT-Diff, a data-driven generative audio model that can, once trained, be used for solving various different audio inverse problems in a problem-agnostic setting.

Analysing Diffusion-based Generative Approaches versus Discriminative Approaches for Speech Restoration

sp-uhh/sgmse 4 Nov 2022

In this paper, we systematically compare the performance of generative diffusion models and discriminative approaches on different speech restoration tasks.