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Ambiscape

CI docs PyPI version Python License: MIT

Ambiscape is a Python toolbox for analysing soundscapes—the sonic ambiences of rooms and other places. It reads mono, stereo, binaural, or first-order ambisonic recordings of any length and describes a place's sound as a whole: level, spectrum, space, rhythm, sources, and more. Several recorders spread through a building can be read together as one acoustic network.

Install

pip install ambiscape

Optional extras add psychoacoustic indicators, machine listening, music analysis, live capture, and spatial visuals. See the install guide.

Quickstart

Point analyze at a session—a folder of WAV files from one recording occasion:

ambiscape analyze my-session/

This streams the audio in constant memory, however long it is. It extracts features, computes descriptors (Leq, LAeq, percentile levels, event statistics, diffuseness, and more), renders overview figures, and writes a README.md summarising the session. Start by reading that README and looking at analysis/overview.png:

Session overview figure: level timeline, spectrogram, anglegram, and diffuseness lane on one clock. The quickstart guide continues from there, on the command line and in Python.

Commands

analyze is one of nearly forty subcommands. The others cover taxonomy annotation, rhythm and tonality, room acoustics and impulse responses, ecological and source-domain indices, perceptual surveys, multi-recorder building networks (network), corpus aggregation, and privacy-aware publishing. The command overview lists them all; ambiscape --help prints the same list.

Documentation

  • User guide & API reference—the session model, feature and descriptor definitions, and a page per analysis module.
  • Wiki—field-recording protocol, recipes, worked case studies, design rationale, and research context.

Ambiscape analyses sound; its sister toolbox MGT-python analyses video. The two meet at file boundaries—see Working with other packages.

Licence

MIT—see LICENSE.

Credits

Ambiscape is developed as part of the AMBIENT project at fourMs / RITMO, University of Oslo, supported by the Research Council of Norway. It is the streaming companion to ambiviz, which renders rich spatial visuals from short ambisonic files.

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A toolbox for analysing soundscapes from mono, stereo, binaural, or ambisonic recordings

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