The Sea-Floor Ears That Heard Six Million Whale Songs

Machines on the Atlantic sea floor that were put there to study rocks deep inside the Earth also recorded whale songs, and an AI that human experts trained found more than 6.3 million fin whale calls in about 43 years' worth of recordings.

Wow picture

Picture the dark floor of the Atlantic Ocean near the Azores, Madeira and the Canary Islands. Dozens of seismometers sit there quietly, feeling the planet's rumbles. Overhead, a fin whale about as long as two school buses sings notes so low that people can barely hear them. Each note shows up as a little smudge at the bottom of a "sound picture" (a spectrogram), and an AI helper circles every smudge: more than six million of them.

"Sea-floor ears" is our show's nickname for ocean-bottom seismometers, and the host says so on air. It is not the scientists' term.

Key facts used in the episode

• 46 ocean-bottom seismometer stations from two networks (São Jorge and UPFLOW) in the Azores–Madeira–Canaries region of the North Atlantic. The recordings run from June 2021 to February 2023.

• 378,912 hours of recordings in total, which is about 43 years if played back to back.

• The AI found 6,291,626 fin whale calls (about 6.3 million). The authors call it the largest fin whale call catalogue to date.

• Human experts hand-marked nearly 40,000 calls to train the AI.

• About 97% precision overall (94% at São Jorge, 97% at UPFLOW). The AI also missed many quieter calls (recall was about 33% at UPFLOW), so the true number of calls is higher.

• Processing one day of recordings from one station took about 15–20 seconds.

• Calling peaked from October to February. There were three recurring song "beats" (gaps of about 12, 16 and 20 seconds between notes), and the most common one shifted during the season.

• The authors describe a possible southward movement of whales as speculative.

• Fin whales are the second-largest whale species, 75–85 feet long (NOAA).

Sources

• Japnanto, J. et al. "Large-scale bioacoustic detection using semantic segmentation: a deep learning framework applied to fin whale calls in ocean-bottom seismometer recordings." arXiv preprint 2609.13281. v1 was posted September 8, 2026 and v2 on September 29, 2026. It has not been peer-reviewed. Authors are from University College London, the University of the Azores (OKEANOS), CSIC Barcelona and the University of St Andrews.

  • Abstract: https://arxiv.org/abs/2609.13281

  • Full text: https://arxiv.org/html/2609.13281v1

• NOAA Fisheries, "Fin Whale" species page (size, second-largest whale, U.S. endangered listing): https://www.fisheries.noaa.gov/species/fin-whale

• Background on related work (a different team using AI to detect Bryde's whale calls in seismic data, June 2026): https://www.seismosoc.org/news/ai-model-hears-whale-calls-in-seismic-data/

• Optional mission tool for families: Chrome Music Lab Spectrogram: https://musiclab.chromeexperiments.com/Spectrogram/

Coach vs copy machine

The AI did the listening, but people taught it, checked its work, and openly said what they still don't know. Kids can use AI the same way. Don't ask "Write my whale report." Ask "Quiz me about fin whales."

Kid Mission of the Week: Make Your Own Sound Picture

1. Draw an arrow across your paper from left to right. That's time.

2. Low sounds go near the bottom of the page and high sounds near the top.

3. Sit still for one minute and draw every sound you hear. A humming fridge might be a long low line, and a bird tweet might be a tiny high dot.

4. Does any sound repeat, like a whale's beat? Count it!

5. Bonus, with a grown-up: Ask an AI helper: "I drew a sound picture. Don't fix it for me. Ask me three questions to help me make it better." Families can also try the free Chrome Music Lab Spectrogram to see their own voices as a real sound picture. It needs microphone permission, so a grown-up should turn it on.