This tool allows to introduce controlled degradations to audio.
Applications:
- evaluate Music Information Systems under different degrees of degradations
- prepare augmented data for training of machine learning systems
It is similar to the [Audio Degradation Toolbox in Matlab by Sebastian Ewert and Matthias Mauch][1], but simpler, and in python. I'm using it for creating my own synthetic datasets.
For the moment, it only works with .WAV files with codec pcm_s16le (16 bits .WAV).
- mp3 compression
- gain
- normalization
- add background noise: [white-noise, brown-noise, ambience-pub, old-vinyl, hum, applause]
- apply smartphone-like distortion
- apply classroom reverb
- apply dynamic range compression
- apply time-stretching
- apply pitch-shifting
- apply equalization
All of them can be combined sequentially in the specified order.
usage: python audio_degrader.py [-h] [--testing]
input_wav [degradation,value [degradation,value ...]]
output_wav
Process audio with a sequence of degradations
Accepted degradadations:
mp3,quality: Mp3 compression. Value is quality (1-5)
gain,db: Gain. Value is dB (e.g. gain,-20.3).
normalize,percentage: Normalize. Percentage in 0.0-1.0 (1.0=full range)
white-noise,snr: Add white noise. SNR in dB.
brown-noise,snr: Add brown noise. SNR in dB.
ambience-pub,snr: Add pub ambience. SNR in dB.
vinyl,snr: Add vinyl noise. SNR in dB.
hum,snr: Add hum noise. SNR in dB.
applause,snd: Add applause noise. SNR in dB.
smartphone_mic,level: Smartphone_mic-like sonority. Level 0.0-1.0
classroom,level: Classroom-like reverb. Level 0.0-1.0
dr-compression,degree: Dynamic range compression. Degree in (1-3).
time-stretching,ratio: Apply time streting. Ratio in from -9.99 to 9.99
pitch-shifting,ratio: Apply time streting. Ratio in -9.99 to 9.99
eq,freq_hz/bw_hz/gain_db: Apply equalization with sox.
positional arguments:
input_wav Input audio wav
degradation,value List of sequential degradations
output_wav Output audio wav
optional arguments:
-h, --help show this help message and exit
--testing Output audio wav
Note: all audios are transcoded to mono, 8KHz, pcm_s16le
$ python audio_degrader.py test.wav gain,-15 ambience-pub,6 dr-compression,3 mp3,1 gain,15 out.wav
- [
librosa][2] for audio processing in python. Just install it withpip install librosa - [
sox][3] for audio processing via command line. Just install it withapt-get install soxin Linux orbrew install soxin OSX. - [
rubberband][4] for time stretchign and pitch shifting. Install it withapt-get install rubberband-cliorbrew install rubberband. - [
ffmpeg][5] for transcoding. Install itapt-get install ffmpegin Linux orbrew install ffmpegin OSX. [1]: https://code.soundsoftware.ac.uk/projects/audio-degradation-toolbox [2]: https://github.com/librosa/librosa [3]: http://sox.sourceforge.net/sox.html [4]: http://breakfastquay.com/rubberband/ [5]: https://www.ffmpeg.org/
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