From Chemnitz University of Technology in Germany:
The AI-powered bird call app developed by a research team from Chemnitz University of Technology and Cornell University that already recognizes more than 3,000 bird calls worldwide now runs on iOS devices.
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The app was developed by Chemnitz University of Technology and Cornell University (USA) and can identify 3,000 bird species based on their song using an AI algorithm.
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Recognizing bird calls is an elaborate process. That’s because the core of the app is an AI-powered algorithm connected to a server at Chemnitz University of Technology. An artificial neural network determines the recorded bird voice when a request is made. Kahl and the team therefore had to ensure that the speed of the app would not suffer as the number of users – and thus search queries – and bird species increased. But [Dr. Stefan] Kahl assures us that they succeeded. Among other things, she recently successfully completed a test run with a friendly research team from India. Here, too, the identification rate of native bird species was 80 to 85 percent:
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The BirdNET app at a glance
- Automatic recognition of bird calls is based on short audio excerpts
- App displays a visualization of the bird call’s sound wave – users can see what the call looks like
- Based on the audio data, but also on location and date, the app decides whether a particular bird species can be heard.
- Once a species has been identified, details are displayed.
- Observations can be saved and shared with friends.
- Each observation is registered anonymously and evaluated for research purposes.
- Feedback from users is continuously incorporated into the design of the app and the features implemented.
- The app is designed to help people get to know their environment better and, ideally, to increase their ecological awareness.
The increase in identifiable bird species from 1,000 to 3,000 within three years is significant because the app can now be used worldwide. The research team had initially limited the first phase of app programming to the most common species in Europe and North America. Now, people around the world can identify their native songbirds. Another innovation concerns the app’s platform. BirdNET is now available for iOS devices.
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Background: BirdNet and Privacy
The BirdNET app is designed to be data-saving and to protect the privacy of its users. In order for the app to identify songbirds, audio data must be transmitted. Location data is needed to study the migration patterns and distribution of songbirds. The transmission of this data is completely anonymous. Only a randomly generated device identifier is transmitted. The transmitted data is used exclusively for research purposes. Furthermore, the data will be stored exclusively on servers at Chemnitz University of Technology.
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