{"id":89203,"date":"2020-10-14T21:10:46","date_gmt":"2020-10-14T18:10:46","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/algorithm-discovers-that-every-lion-has-a-unique-and-trackable-roar\/"},"modified":"2020-10-14T21:10:46","modified_gmt":"2020-10-14T18:10:46","slug":"algorithm-discovers-that-every-lion-has-a-unique-and-trackable-roar","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/algorithm-discovers-that-every-lion-has-a-unique-and-trackable-roar\/","title":{"rendered":"#Algorithm discovers that every lion has a unique and trackable roar"},"content":{"rendered":"

“#Algorithm discovers that every lion has a unique and trackable roar<\/strong>”<\/p>\n

\n Scientists from Oxford University have used a\u00a0machine learning\u00a0algorithm to discover every lion has its own identifiable and trackable roar.<\/p>\n

Previous\u00a0research has shown that lions roar to communicate with other members of their pride and\u00a0scare off foes. But we still know little about how they recognize which animal has made the call.<\/span><\/p>\n

The Oxford scientists tried to find out by designing a\u00a0device called a \u201cbiologger\u201d that\u2019s attached to a lion\u2019s existing GPS collar to record audio and movement data. They then associated each call with a lion by cross-referencing the data through their recordings of roars.<\/p>\n

[Read:\u00a0This AI system thinks we\u2019re getting better at wildlife conservation]<\/em><\/p>\n

Next, the\u00a0team\u00a0used the data collected by the biologgers to train a pattern recognition algorithm to recognize each lion\u2019s roar. Finally, they tested the algorithm on recordings it had not been fed before.<\/p>\n

They found that each lion\u2019s roar produces a distinctive frequency shape. The algorithm\u00a0used these to match a roar to an individual lion with 91.5% accuracy.<\/p>\n

\"\"
Credit: WildCRU<\/figcaption>
<\/a>The red line shows the fundamental frequency of a lion\u2019s roar.<\/figcaption><\/figure>\n

The system was developed by researchers from Oxford University\u2019s\u00a0Department of Computer Science<\/a> and WildCru, the conservation unit that had been tracking Cecil the Lion until he was killed by a trophy hunter in 2015<\/a>.\u00a0His death sparked an outcry that forced the hunter into hiding.<\/p>\n

Identifying the roars of other lions could help protect the roughly 20,000 of them<\/a> that are still left in the wild.<\/p>\n

\u201cAfrican lion numbers are declining and developing cost-effective tools for monitoring, and ultimately better protecting, populations is a conservation priority,\u201d said WildCRU\u2019s\u00a0Andrew J. Loveridge. \u201cThe ability to remotely evaluate the number of individual lions in a population from their roars could revolutionize the way in which lion populations are assessed.\u201d<\/p>\n

You can read the full research paper\u00a0in the journal Bioacoustics<\/a>.<\/p>\n

\n Published October 14, 2020 \u2014 18:10 UTC\n <\/p>\n<\/p><\/div>\n