# A Real-Time Wideband Neural Vocoder at 1.6 kb/s Using LPCNet

arXiv: https://arxiv.org/abs/1903.12087 · HTML: https://mlsanity.com/paper/1903.12087/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Mar 2019.

## Built on by (most cited first, 16 of 16)

- [High Fidelity Neural Audio Compression](https://mlsanity.com/paper/2210.13438/) (2022)
- [Speech Resynthesis from Discrete Disentangled Self-Supervised Representations](https://mlsanity.com/paper/2104.00355/) (2021)
- [A Survey on Neural Speech Synthesis](https://mlsanity.com/paper/2106.15561/) (2021)
- [WaveFit: An Iterative and Non-autoregressive Neural Vocoder based on Fixed-Point Iteration](https://mlsanity.com/paper/2210.01029/) (2022)
- [FlowDec: A flow-based full-band general audio codec with high perceptual quality](https://mlsanity.com/paper/2503.01485/) (2025)
- [Generative De-Quantization for Neural Speech Codec via Latent Diffusion](https://mlsanity.com/paper/2311.08330/) (2023)
- [Enhancing into the codec: Noise Robust Speech Coding with Vector-Quantized Autoencoders](https://mlsanity.com/paper/2102.06610/) (2021)
- [HARP-Net: Hyper-Autoencoded Reconstruction Propagation for Scalable Neural Audio Coding](https://mlsanity.com/paper/2107.10843/) (2021)
- [Scalable and Efficient Neural Speech Coding: A Hybrid Design](https://mlsanity.com/paper/2103.14776/) (2021)
- [A Streamwise GAN Vocoder for Wideband Speech Coding at Very Low Bit Rate](https://mlsanity.com/paper/2108.04051/) (2021)
- [NESC: Robust Neural End-2-End Speech Coding with GANs](https://mlsanity.com/paper/2207.03282/) (2022)
- [FlowMAC: Conditional Flow Matching for Audio Coding at Low Bit Rates](https://mlsanity.com/paper/2409.17635/) (2024)
- [Neural Speech and Audio Coding: Modern AI Technology Meets Traditional Codecs](https://mlsanity.com/paper/2408.06954/) (2024)
- [AudioFormer: Audio Transformer learns audio feature representations from discrete acoustic codes](https://mlsanity.com/paper/2308.07221/) (2023)
- [The Equalizer: Introducing Shape-Gain Decomposition in Neural Audio Codecs](https://mlsanity.com/paper/2602.15491/) (2026)
- [Neural Speech Synthesis on a Shoestring: Improving the Efficiency of LPCNet](https://mlsanity.com/paper/2202.11169/) (2022)

## Abstract (arXiv)

Neural speech synthesis algorithms are a promising new approach for coding speech at very low bitrate. They have so far demonstrated quality that far exceeds traditional vocoders, at the cost of very high complexity. In this work, we present a low-bitrate neural vocoder based on the LPCNet model. The use of linear prediction and sparse recurrent networks makes it possible to achieve real-time operation on general-purpose hardware. We demonstrate that LPCNet operating at 1.6 kb/s achieves significantly higher quality than MELP and that uncompressed LPCNet can exceed the quality of a waveform codec operating at low bitrate. This opens the way for new codec designs based on neural synthesis models.