The ‘microfaune’ (or ‘micro-fauna’ in English) project was started last September within our research division at Wazo, the NGO I co-founded. Microfaune aims to develop machine-learning tools for bioacoustics research, in order to foster birds and wildlife conservation in cities.
The goal of the project is to improve the assessment of urban biodiversity with deep learning algorithms. A first step involves the detection of birdsong from audio recordings, made at the Cité Universitaire de Paris using devices provided by the Cornell University Laboratory of Ornithology. The contributions of this project are:
A platform for annotating bird songs (presence or absence)
A model allowing the rapid identification chunking and labelling of bird songs
An open-source labelled database
The project, led by Hadrien Jean and his team, was selected for the Fall 2019 and Fall 2020 season of DataForGood, the French incubator for common good which provide AI resources and solutions for the future of humanity.
Thanks to the wonderful work of Doby Rahnev, the Confidence Database is now out as a resource in Nature Human Behaviour. More than 80 authors from all over the world contributed their datasets. The database, which is still growing, includes more than 8,700 participants (almost 4 million trials).
Wazo – Cité internationale des Oiseaux, a France-based NGO I co-founded two years ago to fight biodiversity decline in cities, has been awarded the prestigious Medal of Honor of the City of Paris. Wazo develops machine-learning algorithms and bioacoustics tools for birds and wildlife conservation. We are particularly involved in certain parks in Paris (e.g. the Cité internationale universtaire park, in the 14th arrondissement).