# A Neural Vocoder Based Packet Loss Concealment Algorithm

arXiv: https://arxiv.org/abs/2203.14010 · HTML: https://mlsanity.com/paper/2203.14010/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Mar 2022.

## Built on by (most cited first, 1 of 1)

- [Is Self-Supervised Learning Enough to Fill in the Gap? A Study on Speech Inpainting](https://mlsanity.com/paper/2405.20101/) (2024)

## Abstract (arXiv)

The packet loss problem seriously affects the quality of service in Voice over IP (VoIP) sceneries. In this paper, we investigated online receiver-based packet loss concealment which is much more portable and applicable. For ensuring the speech naturalness, rather than directly processing time-domain waveforms or separately reconstructing amplitudes and phases in frequency domain, a flow-based neural vocoder is adopted to generate the substitution waveform of lost packet from Mel-spectrogram which is generated from history contents by a well-designed neural predictor. Furthermore, a waveform similarity-based smoothing post-process is created to mitigate the discontinuity of speech and avoid the artifacts. The experimental results show the outstanding performance of the proposed method.