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Home / Science / Lions Roar: AI Uncovers Secret Second Sound

Lions Roar: AI Uncovers Secret Second Sound

21 Nov, 2025

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Summary

  • Researchers discovered a second lion roar using AI.
  • This new 'intermediary roar' is flatter and follows the full roar.
  • AI aids conservation by improving population monitoring.
Lions Roar: AI Uncovers Secret Second Sound

Researchers from the University of Exeter have unveiled a previously unknown vocalization in African lions, dubbed the "intermediary roar." This discovery was made possible through the application of artificial intelligence, which analyzed recordings from Nyerere National Park in Tanzania. Unlike the familiar, powerful full-throated roar, the intermediary roar is described as a flatter sound with less pitch variation, and it always follows the full roar within a vocalization bout.

This new finding expands our knowledge of lion communication, which plays a crucial role in territorial signaling and social interactions. The AI-based methodology offers a more objective and accessible alternative to traditional human-led acoustic analysis. This advancement is particularly significant for conservationists, as the AI can now more reliably estimate lion population sizes and monitor individual animals within dwindling populations.

The potential applications of this AI technology extend beyond simply identifying different roars. It can distinguish individual lions, offering a powerful tool for wildlife management and the protection of this iconic species. The research highlights how innovative technology can significantly enhance our ability to study and conserve wildlife.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
Researchers discovered a new 'intermediary roar' that lions make, in addition to their well-known full-throated roar.
Scientists used artificial intelligence (AI) to analyze lion vocalizations recorded in Tanzania's Nyerere National Park.
AI can more accurately monitor lion populations and individual animals by analyzing their unique vocal signatures.

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