SNAC: Multi-Scale Neural Audio Codec
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Abstract (arXiv)
Neural audio codecs have recently gained popularity because they can represent audio signals with high fidelity at very low bitrates, making it feasible to use language modeling approaches for audio generation and understanding. Residual Vector Quantization (RVQ) has become the standard technique for neural audio compression using a cascade of VQ codebooks. This paper proposes the Multi-Scale Neural Audio Codec, a simple extension of RVQ where the quantizers can operate at different temporal resolutions. By applying a hierarchy of quantizers at variable frame rates, the codec adapts to the audio structure across multiple timescales. This leads to more efficient compression, as demonstrated by extensive objective and subjective evaluations. The code and model weights are open-sourced at https://github.com/hubertsiuzdak/snac.
Key facts. Cited by 43 papers in the map (data through 14 Oct 2026). Builds on 18 of its 28 references that are in the map. First posted on arXiv 18 Oct 2024.
Builds on
18 of 28 references.
References · 18
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- 2020Longformer: The Long-Document Transformercited by 3,413
- 2019Generating Diverse High-Fidelity Images with VQ-VAE-2cited by 1,387
- 2020HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesiscited by 1,154
- 2021SoundStream: An End-to-End Neural Audio Codeccited by 771
- 2022High Fidelity Neural Audio Compressioncited by 687
- 2022AudioLM: a Language Modeling Approach to Audio Generationcited by 616
- 2020Jukebox: A Generative Model for Musiccited by 542
- 2023Simple and Controllable Music Generationcited by 488
- 2023High-Fidelity Audio Compression with Improved RVQGANcited by 431
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- 2022BigVGAN: A Universal Neural Vocoder with Large-Scale Trainingcited by 251
- 2018A Hierarchical Latent Vector Model for Learning Long-Term Structure in Musiccited by 131
- 2021UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generationcited by 74
- 2018The challenge of realistic music generation: modelling raw audio at scalecited by 63
- 2019Low Bit-Rate Speech Coding with VQ-VAE and a WaveNet Decodercited by 49
- 2017End-to-End Optimized Speech Coding with Deep Neural Networkscited by 22
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Citing papers per year: 2024: 3; 2025: 20; 2026: 20.
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12 most cited of 33 All 33 (JSON)
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