Visualization of long-duration acoustic recordings of the environment

Towsey, Michael, Zhang, Liang, Cottman-Fields, Mark, Wimmer, Jason, Zhang, Jinglan, & Roe, Paul (2014) Visualization of long-duration acoustic recordings of the environment. Procedia Computer Science, 29, pp. 703-712.

View at publisher (open access)


Acoustic recordings of the environment are an important aid to ecologists monitoring biodiversity and environmental health. However, rapid advances in recording technology, storage and computing make it possible to accumulate thousands of hours of recordings, of which, ecologists can only listen to a small fraction. The big-data challenge addressed in this paper is to visualize the content of long-duration audio recordings on multiple scales, from hours, days, months to years. The visualization should facilitate navigation and yield ecologically meaningful information.

Our approach is to extract (at one minute resolution) acoustic indices which reflect content of ecological interest. An acoustic index is a statistic that summarizes some aspect of the distribution of acoustic energy in a recording. We combine indices to produce false-color images that reveal acoustic content and facilitate navigation through recordings that are months or even years in duration.

Impact and interest:

15 citations in Scopus
Search Google Scholar™
13 citations in Web of Science®

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 74420
Item Type: Journal Article
Refereed: Yes
Additional Information: Proceedings of 2014 International Conference on Computational Science
Keywords: Acoustic recordings, Environment, Biodiversity monitoring, Big data, Visualization
DOI: 10.1016/j.procs.2014.05.063
ISSN: 1877-0509
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 Elsevier B.V.
Deposited On: 27 Jul 2014 23:23
Last Modified: 11 Aug 2014 02:59

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page