Augmenter that apply mask operation to audio.
MaskAug(sampling_rate=None, zone=(0.2, 0.8), coverage=1.0, duration=None, mask_with_noise=True, name='Mask_Aug', verbose=0, stateless=True)¶
- sampling_rate (int) – Sampling rate of input audio. Mandatory if duration is provided.
- zone (tuple) – Assign a zone for augmentation. Default value is (0.2, 0.8) which means that no any augmentation will be applied in first 20% and last 20% of whole audio.
- coverage (float) – Portion of augmentation. Value should be between 0 and 1. If 1 is assigned, augment operation will be applied to target audio segment. For example, the audio duration is 60 seconds while zone and coverage are (0.2, 0.8) and 0.7 respectively. 42 seconds ((0.8-0.2)*0.7*60) audio will be augmented.
- duration (int) – Duration of augmentation (in second). Default value is None. If value is provided. coverage value will be ignored.
- mask_with_noise (bool) – If it is True, targeting area will be replaced by noise. Otherwise, it will be replaced by 0.
- name (str) – Name of this augmenter
>>> import nlpaug.augmenter.audio as naa >>> aug = naa.MaskAug(sampling_rate=44010)
augment(data, n=1, num_thread=1)¶
- data (object/list) – Data for augmentation. It can be list of data (e.g. list of string or numpy) or single element (e.g. string or numpy). Numpy format only supports audio or spectrogram data. For text data, only support string or list of string.
- n (int) – Default is 1. Number of unique augmented output. Will be force to 1 if input is list of data
- num_thread (int) – Number of thread for data augmentation. Use this option when you are using CPU and n is larger than 1
>>> augmented_data = aug.augment(data)