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AddBackgroundNoise

Added in v0.9.0

Mix in another sound, e.g. a background noise. Useful if your original sound is clean and you want to simulate an environment where background noise is present.

Can also be used for mixup when training classification/annotation models.

A path to a file/folder with sound(s), or a list of file/folder paths, must be specified. These sounds should ideally be at least as long as the input sounds to be transformed. Otherwise, the background sound will be repeated, which may sound unnatural.

Note that in the default case (noise_rms="relative") the gain of the added noise is relative to the signal level in the input. This implies that if the input is completely silent, no noise will be added.

Optionally, the added noise sound can be transformed (with noise_transform) before it gets mixed in.

Here are some examples of datasets that can be downloaded and used as background noise:

Input-output example

Here we add some music to a speech recording, targeting a signal-to-noise ratio (SNR) of 5 Decibels (dB), which means that the speech (signal) is 5 dB louder than the music (noise).

Input-output waveforms and spectrograms

Input sound Transformed sound

Usage examples

from audiomentations import AddBackgroundNoise, PolarityInversion

transform = AddBackgroundNoise(
    sounds_path="/path/to/folder_with_sound_files",
    min_snr_db=3.0,
    max_snr_db=30.0,
    noise_transform=PolarityInversion(),
    p=1.0
)

augmented_sound = transform(my_waveform_ndarray, sample_rate=16000)

from audiomentations import AddBackgroundNoise, PolarityInversion

transform = AddBackgroundNoise(
    sounds_path="/path/to/folder_with_sound_files",
    noise_rms="absolute",
    min_absolute_rms_db=-45.0,
    max_absolute_rms_db=-15.0,
    noise_transform=PolarityInversion(),
    p=1.0
)

augmented_sound = transform(my_waveform_ndarray, sample_rate=16000)

AddBackgroundNoise API

sounds_path: Union[List[Path], List[str], Path, str]
A path or list of paths to audio file(s) and/or folder(s) with audio files. Can be str or Path instance(s). The audio files given here are supposed to be background noises.
min_snr_db: float • unit: Decibel
Default: 3.0. Minimum signal-to-noise ratio in dB. Is only used if noise_rms is set to "relative"
max_snr_db: float • unit: Decibel
Default: 30.0. Maximum signal-to-noise ratio in dB. Is only used if noise_rms is set to "relative"
min_snr_in_db: float • unit: Decibel
⚠ Deprecated as of v0.31.0, removed as of v0.38.0. Use min_snr_db instead
max_snr_in_db: float • unit: Decibel
⚠ Deprecated as of v0.31.0, removed as of v0.38.0. Use max_snr_db instead
noise_rms: str • choices: "absolute", "relative"
Default: "relative". Defines how the background noise will be added to the audio input. If the chosen option is "relative", the root mean square (RMS) of the added noise will be proportional to the RMS of the input sound. If the chosen option is "absolute", the background noise will have an RMS independent of the rms of the input audio file
min_absolute_rms_db: float • unit: Decibel
Default: -45.0. Is only used if noise_rms is set to "absolute". It is the minimum RMS value in dB that the added noise can take. The lower the RMS is, the lower the added sound will be.
max_absolute_rms_db: float • unit: Decibel
Default: -15.0. Is only used if noise_rms is set to "absolute". It is the maximum RMS value in dB that the added noise can take. Note that this value can not exceed 0.
min_absolute_rms_in_db: float • unit: Decibel
⚠ Deprecated as of v0.31.0, removed as of v0.38.0. Use min_absolute_rms_db instead
max_absolute_rms_in_db: float • unit: Decibel
⚠ Deprecated as of v0.31.0, removed as of v0.38.0. Use max_absolute_rms_in_db instead
noise_transform: Optional[Callable[[NDArray[np.float32], int], NDArray[np.float32]]]
Default: None. A callable waveform transform (or composition of transforms) that gets applied to the noise before it gets mixed in. The callable is expected to input audio waveform (numpy array) and sample rate (int).
p: float • range: [0.0, 1.0]
Default: 0.5. The probability of applying this transform.
lru_cache_size: int
Default: 2. Maximum size of the LRU cache for storing noise files in memory

Source code

audiomentations/augmentations/add_background_noise.py