ENSO的初步音化：传统爪哇甘美兰音阶
Preliminary sonification of ENSO using traditional Javanese gamelan scales
AI总结：
本文利用传统爪哇甘美兰五声音阶对ENSO进行音化，通过四种创作策略将尼诺3.4指数编码为二维声学相空间轨迹，揭示了音化方法在复杂系统诊断中的动态特征。
摘要：
音化——将数据映射到非语音音频——为表示复杂动力系统提供了一个未被充分探索的通道。我们将厄尔尼诺-南方涛动（ENSO），一个低维气候混沌的典型例子，作为文化情境音化的测试案例，通过复杂系统诊断进行评估。使用参数映射音化将尼诺3.4海表温度异常指数（1870-2024）编码为两个传统爪哇甘美兰五声音阶（pelog和slendro）的四个创作策略，然后将结果音频分析为二维声学相空间中的轨迹。基于复发的诊断、凸包几何和耦合分析发现，音化流程保留了关键的动力学特征：交替模式产生最高的轨迹复发率，反映了ENSO的准周期性；分层多声部模式探索了最广的相空间区域；而两种音阶家族导致了谱亮度和能量之间质的不同耦合区域——主要在pelog中为反相，在slendro中则近似独立。相空间轨迹分析为在复杂系统背景下比较音化设计提供了严格的几何框架。感知验证仍需进行；我们贡献了用于评估此类映射的动力学系统方法论。
英文摘要：
Sonification -- the mapping of data to non-speech audio -- offers an underexplored channel for representing complex dynamical systems. We treat El Niño-Southern Oscillation (ENSO), a canonical example of low-dimensional climate chaos, as a test case for culturally-situated sonification evaluated through complex systems diagnostics. Using parameter-mapping sonification of the Niño 3.4 sea surface temperature anomaly index (1870--2024), we encode ENSO variability into two traditional Javanese gamelan pentatonic systems (pelog and slendro) across four composition strategies, then analyze the resulting audio as trajectories in a two-dimensional acoustic phase space. Recurrence-based diagnostics, convex hull geometry, and coupling analysis reveal that the sonification pipeline preserves key dynamical signatures: alternating modes produce the highest trajectory recurrence rates, echoing ENSO's quasi-periodicity; layered polyphonic modes explore the broadest phase space regions; and the two scale families induce qualitatively distinct coupling regimes between spectral brightness and energy -- predominantly anti-phase in pelog but near-independent in slendro. Phase space trajectory analysis provides a rigorous geometric framework for comparing sonification designs within a complex systems context. Perceptual validation remains necessary; we contribute the dynamical systems methodology for evaluating such mappings.
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