基于Opus编解码器评估有损音乐音频压缩的感知透明性
Evaluating perceptual transparency of lossy music audio compression with Opus codec
AI总结：
本研究采用双盲框架结合LMM、TOST等方法，评估Opus编解码器的感知透明性，发现160kbps码率在关键聆听环境下对未压缩CD音质达到感知透明性。
摘要：
尽管开源Opus音频编解码器被广泛用于数字音频流传输，但其在高码率音乐压缩中的感知透明性阈值仍未得到充分评估。为确定该阈值，本研究采用ITU-R BS.1116-3双盲框架，分两个阶段对Opus进行评估，使用线性混合效应模型（LMM）和双向单侧检验（TOST）分析差异等级以开展统计研究。第一阶段有21名合格听众和23段音乐样本，结果显示128kbps码率下音频与未压缩参考信号在统计上无法区分（p=0.456），但在严格等价性检验中仅以微弱差距未通过（p=0.064）。第二阶段采用最佳线性无偏预测器（BLUP）筛选出10名最关键听众和8个最具挑战性样本进行压力测试，在最坏情况下，128kbps码率下的音频被明确检测出存在失真（p=0.030），而160kbps码率下的音频则成功达到感知透明性（p=0.747）且通过严格统计等价性检验（p=0.024）。本研究得出结论：在关键聆听环境中，160kbps码率的Opus压缩对未压缩CD音质表现出感知透明性。为便于结果复现，研究公开了两个阶段的结果、匿名化的受试者背景信息及样本特征。
英文摘要：
Although the open-source Opus audio codec is widely used for digital audio streaming, its perceptual transparency threshold for high-bitrate music compression remains insufficiently evaluated. To establish this threshold, this study evaluates Opus across a two-phase ITU-R BS.1116-3 double-blind framework, analyzing Difference Grades using a Linear Mixed-Effects Model (LMM) and Two One-Sided Tests (TOST) for statistical equivalence. In a first phase with 21 qualified listeners and 23 music excerpts, 128 kbps achieves statistical in-distinguishability ($p = 0.456$) but narrowly fails strict equivalence to the uncompressed reference ($p = 0.064$). In Phase 2, Best Linear Unbiased Predictors (BLUPs) isolate the 10 most critical listeners and 8 most challenging samples for a stress-test. Under these worst-case conditions, 128 kbps is conclusively detected as degraded ($p = 0.030$), whereas 160 kbps successfully reaches perceptual transparency ($p = 0.747$) and strict statistical equivalence ($p = 0.024$). The study concludes that 160 kbps demonstrates perceptual transparency to uncompressed CD quality in critical listening environments. For reproducibility, we publicly release results for both phases, anonymized subject background info and sample characteristics.
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