Log Complex Color for Visual Pattern Recognition of Total Sound
This provides a new way for humans to analyze complete audio data visually, though it is incremental in enhancing existing visualization techniques.
The paper tackles the problem of visualizing complete audio data by introducing a complex spectrogram method that plots amplitude as brightness/saturation and phase as hue, enabling precise sound reconstruction from images. This allows humans to use visual pattern recognition on full audio information.
While traditional audio visualization methods depict amplitude intensities vs. time, such as in a time-frequency spectrogram, and while some may use complex phase information to augment the amplitude representation, such as in a reassigned spectrogram, the phase data are not generally represented in their own right. By plotting amplitude intensity as brightness/saturation and phase-cycles as hue-variations, our complex spectrogram method displays both amplitude and phase information simultaneously, making such images canonical visual representations of the source wave. As a result, the original sound may be precisely reconstructed (down to the original phases) from an image, simply by reversing our process. This allows humans to apply our highly developed visual pattern recognition skills to complete audio data in new way.