Towards Bitrate-Efficient and Noise-Robust Speech Coding with Variable Bitrate RVQ
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866913903898787840 |
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| author | Chae, Yunkee Lee, Kyogu |
| author_facet | Chae, Yunkee Lee, Kyogu |
| contents | Residual Vector Quantization (RVQ) has become a dominant approach in neural speech and audio coding, providing high-fidelity compression. However, speech coding presents additional challenges due to real-world noise, which degrades compression efficiency. Standard codecs allocate bits uniformly, wasting bitrate on noise components that do not contribute to intelligibility. This paper introduces a Variable Bitrate RVQ (VRVQ) framework for noise-robust speech coding, dynamically adjusting bitrate per frame to optimize rate-distortion trade-offs. Unlike constant bitrate (CBR) RVQ, our method prioritizes critical speech components while suppressing residual noise. Additionally, we integrate a feature denoiser to further improve noise robustness. Experimental results show that VRVQ improves rate-distortion trade-offs over conventional methods, achieving better compression efficiency and perceptual quality in noisy conditions. Samples are available at our project page: https://yoongi43.github.io/noise_robust_vrvq/. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2506_16538 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Bitrate-Efficient and Noise-Robust Speech Coding with Variable Bitrate RVQ Chae, Yunkee Lee, Kyogu Sound Audio and Speech Processing Residual Vector Quantization (RVQ) has become a dominant approach in neural speech and audio coding, providing high-fidelity compression. However, speech coding presents additional challenges due to real-world noise, which degrades compression efficiency. Standard codecs allocate bits uniformly, wasting bitrate on noise components that do not contribute to intelligibility. This paper introduces a Variable Bitrate RVQ (VRVQ) framework for noise-robust speech coding, dynamically adjusting bitrate per frame to optimize rate-distortion trade-offs. Unlike constant bitrate (CBR) RVQ, our method prioritizes critical speech components while suppressing residual noise. Additionally, we integrate a feature denoiser to further improve noise robustness. Experimental results show that VRVQ improves rate-distortion trade-offs over conventional methods, achieving better compression efficiency and perceptual quality in noisy conditions. Samples are available at our project page: https://yoongi43.github.io/noise_robust_vrvq/. |
| title | Towards Bitrate-Efficient and Noise-Robust Speech Coding with Variable Bitrate RVQ |
| topic | Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2506.16538 |