LifeCLEF Bird Identification Task 2016: The arrival of Deep learning

Hervé Goëau (1) , Hervé Glotin (2) , Willem-Pier Vellinga (3) , Robert Planqué (4) , Alexis Joly (1)

1 ZENITH - Scientific Data Management
2 UTLN - Université de Toulon
3 Xeno-canto foundation
4 Department of Mathematics [Amsterdam]

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.

Mots clés: LifeCLEF; Bird; Song; Call; Species; Retrieval; Audio; Collection; Identification; Fine-grained classification; Evaluation; Benchmark; Bioacoustics; Eco-logical monitoring

Domaines: Informatique [cs]

Hervé Goëau, Hervé Glotin, Willem-Pier Vellinga, Robert Planqué, Alexis Joly. LifeCLEF Bird Identification Task 2016: The arrival of Deep learning. CLEF: Conference and Labs of the Evaluation Forum, Sep 2016, Évora, Portugal. pp.440-449. ⟨hal-01373779⟩