Publications

Feature Representations for Conservation Bioacoustics: Review and Discussion

Published in IJCAI 2021 Workshop on AI for Social Good, 2021

Abstract: Acoustic analysis is becoming a key element of environmental monitoring for wildlife conservation. Passive acoustic recorders can document a variety of vocal animals over large areas and long time horizons, paving the path for machine learning algorithms to identify individual species, estimate abundance, and evaluate ecosystem health. How- ever, such techniques rely on finding meaningful characterizations of calls and soundscapes, capable of capturing complex spatiotemporal, taxonomic, and behavioral structure. This article reviews existing methods for computing informative lower- dimensional features in the context of terrestrial passive acoustic monitoring, and discusses directions for further work.

Recommended citation: Tolkova I. "Feature Representations for Conservation Bioacoustics: Review and Discussion." IJCAI 2021 Workshop on AI for Social Good (2021).

Automatic classification of humpback whale social calls

Published in The Journal of the Acoustical Society of America, 2017

Note: this is an abstract within the ASA proceedings, to accompany an oral presentation; not a full article. This is a result of my 2016 REU project.

Recommended citation: Tolkova, Irina, Lisa Bauer, Antonella Wilby, Ryan Kastner, and Kerri Seger. "Automatic classification of humpback whale social calls." The Journal of the Acoustical Society of America 141, no. 5 (2017): 3605-3605.