AdjustDuration
Added in v0.30.0
Trim or pad the audio to the specified length/duration in samples or seconds. If the input sound is longer than the target duration, pick a random offset and crop the sound to the target duration. If the input sound is shorter than the target duration, pad the sound so the duration matches the target duration.
This transform can be useful if you need audio with constant length, e.g. as input to a machine learning model. The reason for varying audio clip lengths can be e.g.
- the nature of the audio dataset (different audio clips have different lengths)
- data augmentation transforms that change the lengths (e.g. time stretching or convolving with impulse responses without cutting the tail)
Input-output example
Here we input an audio clip and remove a part of the start and the end, so the length of the result matches the specified target length.
| Input sound | Transformed sound |
|---|---|
Usage examples
from audiomentations import AdjustDuration
transform = AdjustDuration(duration_samples=60000, p=1.0)
augmented_sound = transform(my_waveform_ndarray, sample_rate=16000)
from audiomentations import AdjustDuration
transform = AdjustDuration(duration_seconds=3.75, p=1.0)
augmented_sound = transform(my_waveform_ndarray, sample_rate=16000)
AdjustDuration API
duration_samples:int• range: [0, ∞)- Target duration in number of samples.
duration_seconds:float• range: [0.0, ∞)- Target duration in seconds.
padding_mode:str• choices:"silence","wrap","reflect"- Default:
"silence". Padding mode. Only used when audio input is shorter than the target duration. padding_position:str• choices:"start","end"- Default:
"end". The position of the inserted/added padding. Only used when audio input is shorter than the target duration. p:float• range: [0.0, 1.0]- Default:
0.5. The probability of applying this transform.