A library for soundscape synthesis and augmentation
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A library for soundscape synthesis and augmentation

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Please refer to the documentation for details.

For the motivation behind scaper and its applications check out the scaper-paper:

Scaper: A library for soundscape synthesis and augmentation
J. Salamon, D. MacConnell, M. Cartwright, P. Li, and J. P. Bello
In IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), New Paltz, NY, USA, Oct. 2017.


Non-python dependencies

Scaper has two non-python dependencies:

On macOS these can be installed using homebrew:

brew install sox
brew install ffmpeg

On linux you can use your distribution's package manager, e.g. on Ubuntu (15.04 "Vivid Vervet" or newer):

sudo apt-get install sox
sudo apt-get install ffmpeg

NOTE: on earlier versions of Ubuntu ffmpeg may point to a Libav binary which is not the correct binary. If you are using anaconda, you can install the correct version by calling conda install -c conda-forge ffmpeg. Otherwise, you can obtain a static binary from the ffmpeg website.

On windows you can use the provided installation binaries:

Installing Scaper

The simplest way to install scaper is by using pip, which will also install the required python dependencies if needed. To install scaper using pip, simply run:

pip install scaper

To install the latest version of scaper from source, clone or pull the lastest version:

git clone git@github.com:justinsalamon/scaper.git

Then enter the source folder and install using pip to handle python dependencies:

cd scaper
pip install -e .


To help you get started with scaper, please see this step-by-step tutorial.


import scaper
import numpy as np

outfolder = 'audio/soundscapes/'

fg_folder = 'audio/soundbank/foreground/'
bg_folder = 'audio/soundbank/background/'

n_soundscapes = 1000
ref_db = -50
duration = 10.0 

min_events = 1
max_events = 9

event_time_dist = 'truncnorm'
event_time_mean = 5.0
event_time_std = 2.0
event_time_min = 0.0
event_time_max = 10.0

source_time_dist = 'const'
source_time = 0.0

event_duration_dist = 'uniform'
event_duration_min = 0.5
event_duration_max = 4.0

snr_dist = 'uniform'
snr_min = 6
snr_max = 30

pitch_dist = 'uniform'
pitch_min = -3.0
pitch_max = 3.0

time_stretch_dist = 'uniform'
time_stretch_min = 0.8
time_stretch_max = 1.2
# Generate 1000 soundscapes using a truncated normal distribution of start times

for n in range(n_soundscapes):
    print('Generating soundscape: {:d}/{:d}'.format(n+1, n_soundscapes))
    # create a scaper
    sc = scaper.Scaper(duration, fg_folder, bg_folder)
    sc.protected_labels = []
    sc.ref_db = ref_db
    # add background
    sc.add_background(label=('const', 'noise'), 
                      source_file=('choose', []), 
                      source_time=('const', 0))

    # add random number of foreground events
    n_events = np.random.randint(min_events, max_events+1)
    for _ in range(n_events):
        sc.add_event(label=('choose', []), 
                     source_file=('choose', []), 
                     source_time=(source_time_dist, source_time), 
                     event_time=(event_time_dist, event_time_mean, event_time_std, event_time_min, event_time_max), 
                     event_duration=(event_duration_dist, event_duration_min, event_duration_max), 
                     snr=(snr_dist, snr_min, snr_max),
                     pitch_shift=(pitch_dist, pitch_min, pitch_max),
                     time_stretch=(time_stretch_dist, time_stretch_min, time_stretch_max))
    # generate
    audiofile = os.path.join(outfolder, "soundscape_unimodal{:d}.wav".format(n))
    jamsfile = os.path.join(outfolder, "soundscape_unimodal{:d}.jams".format(n))
    txtfile = os.path.join(outfolder, "soundscape_unimodal{:d}.txt".format(n))
    sc.generate(audiofile, jamsfile,