The navigation and visualisation of environmental audio using zooming spectrograms

Towsey, Michael W., Truskinger, Anthony, & Roe, Paul (2015) The navigation and visualisation of environmental audio using zooming spectrograms. In ICDM 2015: International Conference on Data Mining, IEEE, Atlantic City, N.J.

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Acoustic recordings play an increasingly important role in monitoring terrestrial and aquatic environments. However, rapid advances in technology make it possible to accumulate thousands of hours of recordings, more than ecologists can ever listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings on multiple scales, from minutes, hours, days to years. The visualization should facilitate navigation and yield ecologically meaningful information prior to listening to the audio. To construct images, we calculate acoustic indices, statistics that describe the distribution of acoustic energy and reflect content of ecological interest. We combine various indices to produce false-color spectrogram images that reveal acoustic content and facilitate navigation. The technical challenge we investigate in this work is how to navigate recordings that are days or even months in duration. We introduce a method of zooming through multiple temporal scales, analogous to Google Maps. However, the “landscape” to be navigated is not geographical and not therefore intrinsically visual, but rather a graphical representation of the underlying audio. We describe solutions to navigating spectrograms that range over three orders of magnitude of temporal scale. We make three sets of observations:

  1. We determine that at least ten intermediate scale steps are required to zoom over three orders of magnitude of temporal scale;

  2. We determine that three different visual representations are required to cover the range of temporal scales;

  3. We present a solution to the problem of maintaining visual continuity when stepping between different visual representations. Finally, we demonstrate the utility of the approach with four case studies.

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ID Code: 91822
Item Type: Conference Paper
Refereed: Yes
Keywords: visualisation of acoustic data, visual analytics, ecological acoustics, multi-scale analysis, zooming interface
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 IEEE
Deposited On: 13 Jan 2016 23:56
Last Modified: 15 Jan 2016 04:42

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