# SuperCodec: A Neural Speech Codec with Selective Back-Projection Network

arXiv: https://arxiv.org/abs/2407.20530 · HTML: https://mlsanity.com/paper/2407.20530/

## Key facts

- Cited by 6 papers in the map (data through 19 Oct 2026).
- Placed in Vocoders and speech synthesis, one of 11 directions in Speech and audio language models.
- Builds on 16 of its 24 references that are in the map.
- First posted on arXiv 30 Jul 2024.

## Placed in

- Speech and audio language models / [Vocoders and speech synthesis](https://mlsanity.com/speech/vocoders-and-speech-synthesis/)

## Builds on (most cited first, 16 of 16)

- [Neural Discrete Representation Learning](https://mlsanity.com/paper/1711.00937/) (2017)
- [SoundStream: An End-to-End Neural Audio Codec](https://mlsanity.com/paper/2107.03312/) (2021)
- [High Fidelity Neural Audio Compression](https://mlsanity.com/paper/2210.13438/) (2022)
- [Selective Kernel Networks](https://mlsanity.com/paper/1903.06586/) (2019)
- [ViSQOL v3: An Open Source Production Ready Objective Speech and Audio Metric](https://mlsanity.com/paper/2004.09584/) (2020)
- [Wavenet based low rate speech coding](https://mlsanity.com/paper/1712.01120/) (2017)
- [Generative Speech Coding with Predictive Variance Regularization](https://mlsanity.com/paper/2102.09660/) (2021)
- [A Real-Time Wideband Neural Vocoder at 1.6 kb/s Using LPCNet](https://mlsanity.com/paper/1903.12087/) (2019)
- [WARP-Q: Quality Prediction For Generative Neural Speech Codecs](https://mlsanity.com/paper/2102.10449/) (2021)
- [End-to-End Neural Speech Coding for Real-Time Communications](https://mlsanity.com/paper/2201.09429/) (2022)
- [Disentangled Feature Learning for Real-Time Neural Speech Coding](https://mlsanity.com/paper/2211.11960/) (2022)
- [LMCodec: A Low Bitrate Speech Codec With Causal Transformer Models](https://mlsanity.com/paper/2303.12984/) (2023)
- [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)
- [CQNV: A combination of coarsely quantized bitstream and neural vocoder for low rate speech coding](https://mlsanity.com/paper/2307.13295/) (2023)
- [All Information is Necessary: Integrating Speech Positive and Negative Information by Contrastive Learning for Speech Enhancement](https://mlsanity.com/paper/2304.13439/) (2023)

## Built on by (most cited first, 6 of 6)

- [Recent Advances in Discrete Speech Tokens: A Review](https://mlsanity.com/paper/2502.06490/) (2025)
- [Codec-SUPERB @ SLT 2024: A lightweight benchmark for neural audio codec models](https://mlsanity.com/paper/2409.14085/) (2024)
- [FreeCodec: A disentangled neural speech codec with fewer tokens](https://mlsanity.com/paper/2412.01053/) (2024)
- [CodecFake+: Codec-Based Resynthesized Data as a Proxy for Detecting CodecFake Speech](https://mlsanity.com/paper/2501.08238/) (2025)
- [Optimising Neural Speech Codecs for 300bps Communication using Reinforcement Learning](https://mlsanity.com/paper/2605.19541/) (2026)
- [GS-Codec: A Gaussian-Splatting Bottleneck for Neural Audio Coding](https://mlsanity.com/paper/2610.04651/) (2026)

## Abstract (arXiv)

Neural speech coding is a rapidly developing topic, where state-of-the-art approaches now exhibit superior compression performance than conventional methods. Despite significant progress, existing methods still have limitations in preserving and reconstructing fine details for optimal reconstruction, especially at low bitrates. In this study, we introduce SuperCodec, a neural speech codec that achieves state-of-the-art performance at low bitrates. It employs a novel back projection method with selective feature fusion for augmented representation. Specifically, we propose to use Selective Up-sampling Back Projection (SUBP) and Selective Down-sampling Back Projection (SDBP) modules to replace the standard up- and down-sampling layers at the encoder and decoder, respectively. Experimental results show that our method outperforms the existing neural speech codecs operating at various bitrates. Specifically, our proposed method can achieve higher quality reconstructed speech at 1 kbps than Lyra V2 at 3.2 kbps and Encodec at 6 kbps.