Roar Data: Redefining a Lion's Roar Using Machine Learning
Jonathan Growcott, Alex Lobora, Andrew Markham, Charlotte E. Searle, Johan Wahlström, Matthew Wijers, Benno I. Simmons

TL;DR
This paper introduces a machine learning method to automatically identify and classify lion roars, improving population monitoring and reducing human bias.
Contribution
A data-driven approach using simple acoustic metrics and clustering to classify lion roars with high accuracy.
Findings
Lions produce two distinct types of roars: full-throated and intermediary.
Simple metrics like maximum frequency and vocalization length can classify lion calls with 95.4% accuracy.
Automated classification improves individual lion identification compared to manual methods.
Abstract
For territorial advertisement and intra‐pride communication African lions emit a roaring bout, of which one component, is their iconic roar. The full‐throated roar of a lion has recently been shown to be a unique and individually identifiable signature. At the same time, the frequency of large‐scale passive acoustic monitoring surveys has increased. As such, a lion's roar may soon become a useful tool to count individuals and estimate population density, to supplement traditional survey techniques. Currently, selecting full‐throated roars is heavily dependent on expert inference and is therefore subject to human‐induced bias. We propose a data‐driven approach to automatically classify lions' full‐throated roars from the other vocalisations that constitute a roaring bout. By using two‐state Gaussian Hidden‐Markov Models, we also demonstrate that two types of roars exist within a lion's…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAnimal Vocal Communication and Behavior · Marine animal studies overview · Insect and Arachnid Ecology and Behavior
