UC Berkeley leaps ahead in decoding whale talk with AI
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UC Berkeley leaps ahead in decoding whale talk with AI
"It was striking just how structured the system was. I've never seen anything like that before with other animals,"
"We're showing the world that there's more than meets the eye in sperm whales and that, if one cares to look closely, they're not as alien. We're much more similar to each other than we used to think."
"Before, people were looking just at the timing and the number of clicks exchanged between sperm whales, but now we have to look at the frequencies, too. A whole new set of patterns have appeared,"
"Now, it's one of the most complex non-human communication systems we have observed."
Recordings from social units of sperm whales off Dominica (2005–2018) were analyzed with a machine-learning model to identify acoustic patterns. When audio was sped up and the silences between clicks removed, analysis detected spectral features resembling human vowels, particularly the vowels /a/ and /i/, and several vowel combinations. The findings indicate that sperm whale codas involve not only timing and click counts but also frequency structure, revealing a highly structured and complex non-human communication system. Project CETI combined expertise in AI, marine biology, acoustics, cryptography, and robotics to support the multidisciplinary analysis and interpretation.
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