# Deep Long Audio Inpainting

arXiv: https://arxiv.org/abs/1911.06476 · HTML: https://mlsanity.com/paper/1911.06476/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Nov 2019.

## Built on by (most cited first, 8 of 8)

- [Masked Autoencoders that Listen](https://mlsanity.com/paper/2207.06405/) (2022)
- [Speech inpainting: Context-based speech synthesis guided by video](https://mlsanity.com/paper/2306.00489/) (2023)
- [On the Design of Deep Priors for Unsupervised Audio Restoration](https://mlsanity.com/paper/2104.07161/) (2021)
- [Automated Side Channel Analysis of Media Software with Manifold Learning](https://mlsanity.com/paper/2112.04947/) (2021)
- [Correcting Mispronunciations in Speech using Spectrogram Inpainting](https://mlsanity.com/paper/2204.03379/) (2022)
- [Xi-Net: Transformer Based Seismic Waveform Reconstructor](https://mlsanity.com/paper/2406.16932/) (2024)
- [Robust Multi-Modal Speech In-Painting: A Sequence-to-Sequence Approach](https://mlsanity.com/paper/2406.00901/) (2024)
- [Sequence-to-Sequence Multi-Modal Speech In-Painting](https://mlsanity.com/paper/2406.01321/) (2024)

## Abstract (arXiv)

Long (> 200 ms) audio inpainting, to recover a long missing part in an audio segment, could be widely applied to audio editing tasks and transmission loss recovery. It is a very challenging problem due to the high dimensional, complex and non-correlated audio features. While deep learning models have made tremendous progress in image and video inpainting, audio inpainting did not attract much attention. In this work, we take a pioneering step, exploring the possibility of adapting deep learning frameworks from various domains inclusive of audio synthesis and image inpainting for audio inpainting. Also, as the first to systematically analyze factors affecting audio inpainting performance, we explore how factors ranging from mask size, receptive field and audio representation could affect the performance. We also set up a benchmark for long audio inpainting. The code will be available on GitHub upon accepted.