The LifeCLEF bird identification challenge provides a large-scale testbed for the system-oriented evaluation of bird species identification based on audio recordings. One of its main strength is that the data used for the evaluation is collected through Xeno-Canto, the largest network of bird sound recordists in the world. This makes the task closer to the conditions of a real-world application than previous, similar initiatives. The main novelty of the 2016-th edition of the challenge was the inclusion  of soundscape recordings in  addition  to  the  usual  xeno-canto recordings that focus on a single foreground species. This paper reports the methodology of the conducted evaluation, the overview of the systems experimented by the 6 participating research groups and a synthetic analysis of the obtained results.
['Hervé Goëau', 'Hervé Glotin', 'Willem-Pier Vellinga', 'Robert Planqué', 'Alexis Joly']
LifeCLEF Bird Identification Task 2016: The arrival of Deep learning