HomeEducationBreaking The Bird Barrier: Scientist Decodes Zebra Finch Language
Breaking The Bird Barrier: Scientist Decodes Zebra Finch Language | File pic
Scientist wins $100,000 prize for decoding birdsong
Dr Julie Elie of the University of California, Berkeley, has won the 2026 Coller-Dolittle Prize for Two-Way Interspecies Communication, receiving $100,000 for decoding the core vocabulary of zebra finches and advancing research into human-animal communication.
Elie identified the 11 core calls used by zebra finches and decoded their meanings. Her research showed that the birds use distinct calls to announce their identity and activities while recognising one another through individual vocal signatures, regardless of what they are saying. She also found that the birds were more likely to confuse calls with similar meanings than those with similar sounds.
“I’m really super-honoured,” Elie said on winning the prize, adding that she hoped the work was a step forwards in the “great endeavour” to communicate with animals. Prof Yossi Yovel, a zoologist at Tel Aviv University and chair of the judging panel, said the research marked “a key moment in the field”.
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Scientist cracks zebra finches' core vocabulary
The prize was established in 2024 by the Jeremy Coller Foundation, in partnership with Tel Aviv University, to encourage progress in two-way communication between humans and animals. Alongside the annual awards, the foundation has announced a $10 million grand prize for achieving two-way human-animal communication.
Elie chose to study zebra finches because of their highly vocal nature, which provided extensive data for analysis. “The question I asked myself when hearing these chatty songbirds was what are they saying?” she said.
Over more than a decade, she recorded and observed the birds' vocalisations, classifying calls based on the context and the individual bird producing them. She then applied machine learning to analyse how information was encoded in the calls before testing her findings through behavioural experiments.
Machine learning validates birds' language
In one experiment, zebra finches heard different calls after tapping a button. Some calls were followed by seeds as a reward, prompting the birds to learn to skip unrewarding calls over time. Comparing the behaviour to social media use, Elie said the birds moved on from calls much like people scroll past videos that appear uninteresting.
Although the birds occasionally made mistakes, they more often confused calls with similar meanings rather than similar sounds. “Their responses indicated they have a mental imagery of the meaning of their vocalisations,” Elie said. “In other words, that they understand the meaning of their call types.”
Prof Jonathan Birch, a philosopher at the London School of Economics and a member of the judging panel, praised Elie's achievement. “Absolutely phenomenal work” over more than 15 years had resulted in “not just building up a dictionary of the 11 ‘core words’ of the zebra finch’s vocabulary, but also asking the finches themselves, through ingenious experimental techniques, whether she’s got the meanings right. It’s a stunning example of how to move rigorously from recording thousands of calls to understanding their meanings.”
Other shortlisted projects included research by a French team showing African striped mice identify one another through ultrasonic squeaks, a Swiss-US team demonstrating that bonobos combine calls into sequences resembling human sentences, and another French team working with researchers in Côte d’Ivoire to interpret chimpanzee hoos and yelps.
AI fuels hopes for two-way animal communication
Researchers say advances in artificial intelligence and machine learning are accelerating efforts to understand how animals communicate, although significant challenges remain before meaningful two-way communication becomes possible. Yovel said there was still a long way to go.
Jeremy Coller, the British billionaire financier behind the prize, expressed greater confidence. “I’m convinced this is now inevitable,” he said. “It’s inevitable because AI is accelerating so fast. I have absolute conviction we will crack the code by 2030, a breakthrough that will benefit humans and our fellow animals the world over.”