通过可控熵抖动提升音频压缩质量，实测效果优于传统方法。
Optimizing Audio Compression Through Entropy-Controlled Dithering
- 采用熵控制的TPDF抖动与噪声整形结合，适应不同音频特征。
- 在最优alpha条件下，TPDF性能显著优于RPDF，尤其在复杂信号中。
- 提供可调参数插件，适合音频工程师优化压缩流程。
本文研究了音频压缩中的熵控制抖动技术，考察标准与改进型TPDF在不同音频场景（如音高、响度、节奏、乐器变化）下的表现，结合噪声整形与熵控参数。使用VISQOL和STOI等感知质量指标评估性能。结果表明，在最优alpha条件下，基于TPDF的抖动始终优于RPDF，且性能随信号特征变化明显，凸显不同TPDF分布的适用情境。研究强调熵与听觉保真度间的权衡，揭示熵控抖动在增强音频压缩算法中的潜力。此外，本文实现了一款可定制参数的DAW插件，为未来音频压缩技术发展奠定基础。
原文摘要 · Abstract (English)
This paper explores entropy-controlled dithering techniques in audio compression, examining the application of standard and modified TPDFs, combined with noise shaping and entropy-controlled parameters, across various audio contexts, including pitch, loudness, rhythm, and instrumentation variations. Perceptual quality metrics such as VISQOL and STOI were used to evaluate performance. The results demonstrate that TPDF-based dithering consistently outperforms RPDF, particularly under optimal alpha conditions, while highlighting performance variability based on signal characteristics. These findings suggest the situational appropriateness of using various TPDF distributions. This work emphasizes the trade-off between entropy and perceptual fidelity, offering insights into the potential of entropy-controlled dithering as a foundation for enhanced audio compression algorithms. A practical implementation as a Digital Audio Workstation plugin introduces customizable dithering controls, laying the groundwork for future advancements in audio compression algorithms.
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