用声音检查光谱:概念验证和扩展到数据库

J. Trayford, C. Harrison, R. Hinz, M. Blatt, S. Dougherty, A. Girdhar
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引用次数: 1

摘要

我们提出了一种新的方法来检查星系光谱使用声音,通过他们的直接音频表示(“光谱审计”)。我们将讨论它作为视觉方法的补充(或替代)的潜力。我们调查了58名受访者,他们仅使用音频表示来评估30个具有强发射线的光学星系光谱。在三个测试中,每个测试都侧重于从光谱中测量到的不同数量(信噪比、发射在线宽度和通量比),我们发现用户评级与测量数量有很好的相关性。这表明物理信息可以独立地从听频谱听析中收集到。在对这些声音进行评级时,我们注意到上下文的重要性,其中听到的顺序示例可以影响响应。最后,我们将这个有前途的试点研究中使用的方法应用于光谱数据集。我们建议审计允许有效地探索复杂的,空间分辨光谱数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inspecting spectra with sound: proof-of-concept & extension to datacubes
We present a novel approach to inspecting galaxy spectra using sound, via their direct audio representation (‘spectral audification’). We discuss the potential of this as a complement to (or stand-in for) visual approaches. We surveyed 58 respondents who use the audio representation alone to rate 30 optical galaxy spectra with strong emission lines. Across three tests, each focusing on different quantities measured from the spectra (signal-to-noise ratio, emission-line width, & flux ratios), we find that user ratings are well correlated with measured quantities. This demonstrates that physical information can be independently gleaned from listening to spectral audifications. We note the importance of context when rating these sonifications, where the order examples are heard can influence responses. Finally, we adapt the method used in this promising pilot study to spectral datacubes. We suggest that audification allows efficient exploration of complex, spatially-resolved spectral data.
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