Exploring acoustic diversity via soundscape_IR

soundscape_IR is a python-based toolbox of soundscape information retrieval, aiming to assist in the analysis of soundscape recordings. The toolbox is primarily designed for: (1) visualization of soundscape dynamics and (2) audio source separation. Workflows provided by soundscape_IR open new directions to assess acoustic diversity in diverse environments and to acoustically quantify ecological interactions across individual, species, and ecosystem levels.

Getting Started

• Installation instructions
• Quick start
  • Visualizing audio data
  • Model training
  • Deployment and spectrogram reconstruction
  • Run spectrogram detection
  • More tutorials
• Run batch analysis
  • Spectrogram concatenation
  • Source separation and spectrogram detection
  • Adaptive and semi-supervised source separation

Documentation

• Audio visualization
• Audio source separation
• Sound detection and feature extraction
• Local-max detector
• Batch analysis
• Long-term spectrogram maker
• Long-term spectrogram viewer
• Analysis result aggregation

Citing soundscape_IR

Note

If you find this package useful in your research, we would appreciate citations to:

Sun, Y-J, Yen, S-C, & Lin, T-H (2022). soundscape_IR: A source separation toolbox for exploring acoustic diversity in soundscapes. Methods in Ecology and Evolution, 13: 2347-2355. https://doi.org/10.1111/2041-210X.13960

About Marine Ecoacoustics and Informatics Lab (MEIL)

MEIL is based in Biodiversity Research Center, Academia Sinica. Led by Dr. Tzu-Hao Lin, MEIL investigates the applications of ecological informatics in biodiversity monitoring and conservation management. If you’re interested in our work, please check our website or follow us on facebook.

Indices and tables

• Index

• Module Index

• Search Page