Acoustic_Indices

Acoustic_Indices is a Python library to extract global acoustic indices from an audio file for use as a biodiversity proxy, within the framework of Ecoacoustics.

Indices

• Features extraction from Soundscape Ecology

  • Acoustic Complexity Index
  • Acoustic Diversity Index
  • Acoustic Evenness Index
  • Bioacoustic Index
  • Normalized Difference Sound Index
  • Spectral Entropy
  • Temporal Entropy
  • Number of Peaks
  • Wave Signal to Noise Ratio

• Spectral features extraction

  • Spectral centroid
  • Spectrogram
  • Noise removed spectrogram

• Temporal features extraction

  • RMS energy
  • Zero Crossing Rate

Reference

If you use this code, please cite: Patrice Guyot, & Alice Eldridge. (2023). Python implementation of acoustic indices and low level descriptors. Zenodo. https://doi.org/10.5281/zenodo.10391651

Publications

This code have been used in the following scientific papers:

• Martínez-Tabares, F., & Orozco-Alzate, M. (2023). Identifying Acoustic Features to Distinguish Highly and Moderately Altered Soundscapes in Colombia. Inteligencia Artificial, 26(71), 34-45.
• Durbridge, S., & Murphy, D. T. (2023). Assessment of soundscapes using self-report and physiological measures. Acta Acustica, 7, 6.
• Martínez-Tabares, F., & Orozco-Alzate, M. (2022, November). Selection of acoustic features for the discrimination between highly and moderately transformed Colombian soundscapes. In Ibero-American Conference on Artificial Intelligence (pp. 121-132). Cham: Springer International Publishing.
• Sumitani, S., Suzuki, R., Morimatsu, T., Matsubayashi, S., Arita, T., Nakadai, K., & Okuno, H. G. (2020, January). Soundscape Analysis of Bird Songs in Forests Using Microphone Arrays. In 2020 IEEE/SICE International Symposium on System Integration (SII) (pp. 634-639). IEEE.
• Carruthers-Jones, J., Eldridge, A., Guyot, P., Hassall, C., & Holmes, G. (2019). The call of the wild: Investigating the potential for ecoacoustic methods in mapping wilderness areas. Science of the Total Environment, 695, 133797.
• Eldridge, A., Guyot, P., Moscoso, P., Johnston, A., Eyre-Walker, Y., & Peck, M. (2018). Sounding out ecoacoustic metrics: Avian species richness is predicted by acoustic indices in temperate but not tropical habitats. Ecological Indicators, 95, 939-952.

Usage

Test that everything is going well on one audio file:

$python main\_test\_indices.py 

Compute indices from a directory of audio files:

$python  main\_compute\_indices\_from\_dir

This is the pipeline of the processing:

• Get list of indices and features from a Yaml configuration file
• Read WAV files (using scipy)
• For each audio file, compute stats (min, max, mean, median, std, var) for temporal acoustic indices or get global value for other indices
• Output a csv file (with a row for each audio file and a column for each index)

Prerequisites

• Numpy
• Scipy
• Matlplotlib (for graphing)
• PyYAML (to read configuration file)

History

Versions:

• 0.5: New main (main_compute_indices_from_dir) to compute all indices from a directory of audio files
• 0.4: Port from Python 2 to Python 3
• 0.3: New features: wave SNR, spectro noise removed, NB_peaks.
• 0.2: yaml configuration file. Object oriented audio file and index.
• 0.1: First commit

Credits

The following indices are based on the following papers and inspired in part by the R packages [seewave] (https://cran.r-project.org/package=seewave) and [soundecology] (https://cran.r-project.org/package=soundecology)

• Acoustic Complexity Index - Pieretti et al. (2011)
• Acoustic Diversity Index - Villanueva-Rivera et al. (2011)
• Acoustic Evenness Index - Villanueva-Rivera et al. (2011)
• Bioacoustic Index - Boelman, et al. (2007)
• Normalized Difference Sound Index - Kasten et al. (2012)
• Spectral Entropy - Sueur et al. (2008)
• Temporal Entropy - Sueur et al. (2008)

References:

• Boelman NT, Asner GP, Hart PJ, Martin RE. 2007. Multi-trophic invasion resistance in Hawaii: bioacoustics, field surveys, and airborne remote sensing. Ecological Applications 17: 2137-2144.

• Farina A, Pieretti N, Piccioli L (2011) The soundscape methodology for long-term bird monitoring: a Mediterranean Europe case-study. Ecological Informatics, 6, 354-363.

• Kasten, E.P., Gage, S.H., Fox, J. & Joo, W. (2012). The remote environmental assessment laboratory's acoustic library: an archive for studying soundscape ecology. Ecological Informatics, 12, 50-67.

• Pieretti N, Farina A, Morri FD (2011) A new methodology to infer the singing activity of an avian community: the Acoustic Complexity Index (ACI). Ecological Indicators, 11, 868-873.

• Sueur, J., Pavoine, S., Hamerlynck, O. & Duvail, S. (2008) - Rapid acoustic survey for biodiversity appraisal. PLoS ONE, 3(12): e4065.

• Villanueva-Rivera, L. J., B. C. Pijanowski, J. Doucette, and B. Pekin. 2011. A primer of acoustic analysis for landscape ecologists. Landscape Ecology 26: 1233-1246. doi: 10.1007/s10980-011-9636-9.

This research was generously funded by Leverhulme Research Project Grant RPG-2014-403.