# APCodec+: A Spectrum-Coding-Based High-Fidelity and High-Compression-Rate Neural Audio Codec with Staged Training Paradigm

arXiv: https://arxiv.org/abs/2410.22807 · HTML: https://mlsanity.com/paper/2410.22807/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Oct 2024.

## Built on by (most cited first, 4 of 4)

- [Recent Advances in Discrete Speech Tokens: A Review](https://mlsanity.com/paper/2502.06490/) (2025)
- [MagiCodec: Simple Masked Gaussian-Injected Codec for High-Fidelity Reconstruction and Generation](https://mlsanity.com/paper/2506.00385/) (2025)
- [EuleroDec: A Complex-Valued RVQ-VAE for Efficient and Robust Audio Coding](https://mlsanity.com/paper/2601.17517/) (2026)
- [A High-Quality and Low-Complexity Streamable Neural Speech Codec with Knowledge Distillation](https://mlsanity.com/paper/2509.13670/) (2025)

## Abstract (arXiv)

This paper proposes a novel neural audio codec, named APCodec+, which is an improved version of APCodec. The APCodec+ takes the audio amplitude and phase spectra as the coding object, and employs an adversarial training strategy. Innovatively, we propose a two-stage joint-individual training paradigm for APCodec+. In the joint training stage, the encoder, quantizer, decoder and discriminator are jointly trained with complete spectral loss, quantization loss, and adversarial loss. In the individual training stage, the encoder and quantizer fix their parameters and provide high-quality training data for the decoder and discriminator. The decoder and discriminator are individually trained from scratch without the quantization loss. The purpose of introducing individual training is to reduce the learning difficulty of the decoder, thereby further improving the fidelity of the decoded audio. Experimental results confirm that our proposed APCodec+ at low bitrates achieves comparable performance with baseline codecs at higher bitrates, thanks to the proposed staged training paradigm.