NIPS4Bplus: a richly annotated birdsong audio dataset

Veronica Morfi (1) , Yves Bas (2, 3) , Hanna Pamuła (4) , Hervé Glotin (5, 6) , Dan Stowell (1)

1 Department of Electronic & Electrical Engineering [London]
2 CEFE - Centre d’Ecologie Fonctionnelle et Evolutive
3 CESCO - Centre d'Ecologie et des Sciences de la COnservation
4 AGH UST - AGH University of Science and Technology [Krakow, PL]
5 UTLN - Université de Toulon
6 DYNI - DYNamiques de l’Information

Recent advances in birdsong detection and classification have approached a limit due to the lack of fully annotated recordings. In this paper, we present NIPS4Bplus, the first richly annotated birdsong audio dataset, that is comprised of recordings containing bird vocalisations along with their active species tags plus the temporal annotations acquired for them. Statistical information about the recordings, their species specific tags and their temporal annotations are presented along with example uses. NIPS4Bplus could be used in various ecoacoustic tasks, such as training models for bird population monitoring, species classification, birdsong vocalisation detection and classification.

Mots clés: Audio dataset; Bird vocalisations; Ecosystems; Ecoacoustics; Rich annotations; Bioinformatics; Audio signal processing; Bioacoustics

Domaines: Ecologie, Environnement

Veronica Morfi, Yves Bas, Hanna Pamuła, Hervé Glotin, Dan Stowell. NIPS4Bplus: a richly annotated birdsong audio dataset. PeerJ Computer Science, 2019, 5, pp.e223. ⟨10.7717/peerj-cs.223⟩. ⟨hal-02321703⟩