Skip to main content

Measure one or more aspects of one or more audio files.

Project description

analyzeAudio

Measure one or more aspects of one or more audio files.

Note well: FFmpeg & FFprobe binaries must be in PATH

Some options to download FFmpeg and FFprobe at ffmpeg.org.

Some ways to use this package

Use analyzeAudioFile to measure one or more aspects of a single audio file

from analyzeAudio import analyzeAudioFile
listAspectNames = ['LUFS integrated',
                   'RMS peak',
                   'SRMR mean',
                   'Spectral Flatness mean']
listMeasurements = analyzeAudioFile(pathFilename, listAspectNames)

Use getListAvailableAudioAspects to get a crude list of aspects this package can measure

The aspect names are accurate, but the lack of additional documentation can make things challenging. 'Zero-crossing rate', 'Zero-crossing rate mean', and 'Zero-crossings rate', for example, are different from each other. ("... lack of additional documentation ...")

import analyzeAudio
analyzeAudio.getListAvailableAudioAspects()

Use analyzeAudioListPathFilenames to measure one or more aspects of individual file in a list of audio files

Use audioAspects to call an analyzer function by using the name of the aspect you wish to measure

from analyzeAudio import audioAspects
SI_SDR_channelsMean = audioAspects['SI-SDR mean']['analyzer'](pathFilenameAudioFile, pathFilenameDifferentAudioFile)

Retrieve the names of the parameters for an analyzer function with the ['analyzerParameters'] key-name.

from analyzeAudio import audioAspects
print(audioAspects['Chromagram']['analyzerParameters'])

Use whatMeasurements command line tool to list available measurements

(.venv) C:\apps\analyzeAudio> whatMeasurements
['Abs_Peak_count', 'Bit_depth', 'Chromagram', 'Chromagram mean', 'Crest factor', 'DC offset', 'Duration-samples', 'Dynamic range', 'Flat_factor', 'LUFS high', 'LUFS integrated', 'LUFS loudness range', 'LUFS low', 'Max_difference', 'Max_level', 'Mean_difference', 'Min_difference', 'Min_level', 'Noise_floor', 'Noise_floor_count', 'Peak dB', 'Peak_count', 'RMS from waveform', 'RMS from waveform mean', 'RMS peak', 'RMS total', 'RMS_difference', 'RMS_trough', 'SI-SDR mean', 'SRMR', 'SRMR mean', 'Signal entropy', 'Spectral Bandwidth', 'Spectral Bandwidth mean', 'Spectral Centroid', 'Spectral Centroid mean', 'Spectral Contrast', 'Spectral Contrast mean', 'Spectral Flatness', 'Spectral Flatness mean', 'Spectral centroid', 'Spectral crest', 'Spectral decrease', 'Spectral entropy', 'Spectral flatness', 'Spectral flux', 'Spectral kurtosis', 'Spectral mean', 'Spectral rolloff', 'Spectral skewness', 'Spectral slope', 'Spectral spread', 'Spectral variance', 'Tempo', 'Tempo mean', 'Tempogram', 'Tempogram mean', 'Zero-crossing rate', 'Zero-crossing rate mean', 'Zero-crossings rate']

Installation

pip install analyzeAudio

My recovery

Static Badge YouTube Channel Subscribers

CC-BY-NC-4.0

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

analyzeaudio-0.0.12.tar.gz (18.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

analyzeaudio-0.0.12-py3-none-any.whl (19.1 kB view details)

Uploaded Python 3

File details

Details for the file analyzeaudio-0.0.12.tar.gz.

File metadata

  • Download URL: analyzeaudio-0.0.12.tar.gz
  • Upload date:
  • Size: 18.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for analyzeaudio-0.0.12.tar.gz
Algorithm Hash digest
SHA256 70fe2818b35d6ec93a7c97ac4921cd009cea9eb398189e55562d2ae6b953f466
MD5 3fb377c18bd6164528e1fcff7739def4
BLAKE2b-256 b3810f3a7580059d88e2284e10a117b20a399a0fcd7429ff88dd1ef4703c9ceb

See more details on using hashes here.

Provenance

The following attestation bundles were made for analyzeaudio-0.0.12.tar.gz:

Publisher: pypiRelease.yml on hunterhogan/analyzeAudio

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file analyzeaudio-0.0.12-py3-none-any.whl.

File metadata

  • Download URL: analyzeaudio-0.0.12-py3-none-any.whl
  • Upload date:
  • Size: 19.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.12.9

File hashes

Hashes for analyzeaudio-0.0.12-py3-none-any.whl
Algorithm Hash digest
SHA256 c61ae058ec231cc924f9b17bfe4210671045375190f22f37455177fadf343b22
MD5 5666b043f8de9ccdaaf8aa6f630b69d3
BLAKE2b-256 2b1a1a681a3d4ecaf8bf265c9394a9c06851e7df845724c33a4562b53fbe9b7d

See more details on using hashes here.

Provenance

The following attestation bundles were made for analyzeaudio-0.0.12-py3-none-any.whl:

Publisher: pypiRelease.yml on hunterhogan/analyzeAudio

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page