We develop open-access tools to conduct ecoacoustic research.


scikit-maad is an open source python-R toolbox to run unsupervised classification of sounds. link


bambird is an open source Python package that provides a complete workflow to create your own labelling function to build cleaner bird song recording dataset. link


Our github is here.


seewave is an R package dedicated to sound analysis and synthesis, it includes several functions to run ecoacoustic analyses. link


de Baudouin A, Couprie P, Michaud F, Haupert S, Sueur J (2024) – Similarity visualization of soundscapes in ecology and music. link

. Michaud F, Sueur J, Le Cesne M, Haupert S (2023) Unsupervised classification to improve the quality of a bird song recording dataset. Ecological Informatics. link

. Sueur J (2018) – Sound analysis and synthesis with R. Springer, Berlin, 637 p. link

. Sueur J, Aubin T, Simonis C (2008) – seewave: a free modular tool for sound analysis and synthesis. Bioacoustics, 18: 213-226. link

. Ulloa JS, Aubin T, Llusia D, Bouveyron C, Sueur J (2018) – Estimating animal acoustic diversity in tropical environments using unsupervised multiresolution analysis. Ecological Indicators, 90: 346-355. link

. Ulloa JS, Haupert S, Latorre JS, Aubin T, Sueur J (2021) – scikit-maad: An open-source and modular toolbox for quantitative soundscape analysis in Python. Methods et Ecology and Evolution. link

Available here