uh-soundscapes 1.1.4

Read audio data for an event, process it, and create an exportable product.

UH_Soundscapes

Open-access infrasound-adjacent soundscapes

Annotated openly-available low-frequency audio libraries of rocket [1], explosion [2], and hypersonic [3] signatures are provided. We use a decimated version of the Environmental Sound Classification dataset [4] to provide a validated noise vocabulary. Although the data sources vary, a majority are from smartphone and publicly available recordings. The event types are described in open-access published papers [4-9], and a Python open-source repository was developed for accessing, standardizing, and processing the curated data and metadata [10-11]. This work was funded by the Department of Energy National Nuclear Security Administration under Awards DE-NA0003920 (MTV) and DE-NA0003921 (ETI).

Main files in HIGP data repository [11]:

• ASTRA.pkl
• SHAReD.pkl
• OREX_UH_800Hz.pkl
• ESC50_800Hz.pkl
• ESC50_8kHz.pkl
• ESC50_16kHz.pkl

Installation

Use pip:

pip install uh_soundscapes

Please note that in order to run the Jupyter Notebooks included in this repository, you must install uh_soundscapes into the Notebook's python environment.

Overview of essential data fields included in the datasets:

	Signal source	Signal duration	Source locations included	Station locations included
ASTRA.pkl	Rocket launches, 800Hz	Various (5-10 minutes)	All	All
SHAReD.pkl	Explosions and ambient, 800Hz and 8kHz	0.96 seconds	Some	Some
OREX_UH_800Hz.pkl	Hypersonic atmospheric reentry, 800Hz	1.28 seconds	None*	All
ESC50_800Hz.pkl	Environmental sounds (50 classes), downsampled to 800 Hz	5 seconds	None	None
ESC50_8kHz.pkl	Environmental sounds (50 classes), downsampled to 8 kHz	5 seconds	None	None
ESC50_16kHz.pkl	Environmental sounds (50 classes), downsampled to 16 kHz	5 seconds	None	None

*Source locations are not known, but can be estimated from OSIRIS-REx trajectory data.

References

1. Popenhagen, S.K. (2025). Aggregated Smartphone Timeseries of Rocket-Generated Acoustics (ASTRA). https://doi.org/10.7910/DVN/ZKIS2K (accessed on 21 August 2025).
2. Takazawa, S.K. (2024) Smartphone High-Explosive Audio Recordings Dataset (SHAReD). Available online: https://doi.org/10.7910/DVN/ROWODP (accessed on 21 August 2025).
3. Silber, E.A.; Bowman, D.C.; Carr, C.G.; Eisenberg, D.P.; Elbing, B.R.; Fernando, B.; Garcés, M.A.; et al. Geophysical Observations of the 2023 September 24 OSIRIS-REx Sample Return Capsule Reentry. Planet. Sci. J. 2024, 5, 213; https://doi.org/10.3847/PSJ/ad5b5e.
4. K. J. Piczak. ESC: Dataset for Environmental Sound Classification. In Proceedings of the 23rd ACM international conference on multimedia, pp. 1015-1018, ACM, 2015. Paper available in GitHub Repository https://github.com/karolpiczak/ESC-50 (accessed on 21 August 2025).
5. Popenhagen, S.K.; Takazawa, S.K.; Garcés, M.A. Rocket Launch Detection with Smartphone Audio and Transfer Learning. Signals 2025, 6, 41; https://doi.org/10.3390/signals6030041.
6. Popenhagen, S.K.; Garcés, M.A. Acoustic Rocket Signatures Collected by Smartphones. Signals, 2025, 6, 5; https://doi.org/10.3390/signals6010005.
7. Takazawa, S.K.; Popenhagen, S.K.; Ocampo Giraldo, L.A.; Hix, J.D.; Thompson, S.J.; Chichester, D.L.; Zeiler, C.P.; Garcés, M.A. Explosion Detection using Smartphones: Ensemble Learning with the Smartphone High-explosive Audio Recordings Dataset and the ESC-50 Dataset. Sensors, 2024, 24(20), 6688; https://doi.org/10.3390/s24206688.
8. Takazawa, S.K.; Popenhagen, S.K.; Ocampo Giraldo, L.A.; Cárdenas, E.S.; Hix, J.D.; Thompson, S.J.; Chichester, D.L.; Garcés, M.A. A comparison of smartphone and infrasound microphone data from a fuel air explosive and a high explosive. J. Acoust. Soc. Am. 2024, 156, 1509-1523; https://doi.org/10.1121/10.0028379.
9. KC, R. J; Wilson, T; Fox, D; Spillman K.; Garcés M.A.; Elbing B. R. Acoustic Observations of the OSIRIS-REx Sample Return Capsule Re-Entry from Wendover Airport. Seism. Res. Lett. 2025 XX, 1–14; https://doi.org/10.1785/0220250019.
10. UH_Soundscapes, this repository.
11. UH_Soundscapes, aggregated data at https://www.higp.hawaii.edu/archive/isla/UH_Soundscapes/

Troubleshooting

ModuleNotFoundError

If you use VSCode, there may be issues with module imports. You'll need to add the line

"terminal.integrated.env.OSVERSION": {"PYTHONPATH": "${workspaceFolder}"}

to your user.settings.json. OSVERSION is one of: windows, linux, or osx.

You can access the file via the title bar the top of the screen: View -> Command Palette, then choosing Open User Settings (JSON). Add the line above on a new line before the closing brace. You'll have to add a comma to the previous last line of the file, if any.

Once the line is added, your imports should work correctly. If you still have issues, try restarting VS Code.

Example for Windows version (replace with env.osx for Mac):

{
    "files.autoSave": "afterDelay",
    "git.confirmSync": false,
    "terminal.integrated.env.windows": {"PYTHONPATH": "${workspaceFolder}"}
}

pip Timeouts

Some dependencies may not install due to timeouts over VPNs or firewalls. To resolve this, try running

pip --timeout=10000 install 'package_name'

or any arbitrarily large number for the timeout value.

Jupyter Notebook Issues

If the Jupyter Notebook is not recognizing uh_soundscapes imports, create a new python environment for the notebook to run on, and install uh_soundscapes via pip on the new environment.

Jupyter Notebook runs on a virtual environment, so any local changes to the repository code will not be reflected in the Jupyter Notebook files.

The test_readers.py and dataset_standardization.py files contain the same methods detailed in the reader_tutorial and dataset_fusion_tutorial notebooks, respectively. If you are unable to run the notebooks, refer to those files for examples of function uses.