38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
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"""Contains the volume perturb augmentation model."""
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import random
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from mvector.data_utils.audio import AudioSegment
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from mvector.data_utils.augmentor.base import AugmentorBase
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class VolumePerturbAugmentor(AugmentorBase):
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"""添加随机音量扰动的增强模型
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This is used for multi-loudness training of PCEN. See
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https://arxiv.org/pdf/1607.05666v1.pdf
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for more details.
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:param min_gain_dBFS: Minimal gain in dBFS.
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:type min_gain_dBFS: float
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:param max_gain_dBFS: Maximal gain in dBFS.
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:type max_gain_dBFS: float
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"""
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def __init__(self, min_gain_dBFS, max_gain_dBFS):
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self._min_gain_dBFS = min_gain_dBFS
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self._max_gain_dBFS = max_gain_dBFS
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def transform_audio(self, audio_segment: AudioSegment):
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"""Change audio loadness.
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Note that this is an in-place transformation.
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:param audio_segment: Audio segment to add effects to.
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:type audio_segment: AudioSegmenet|SpeechSegment
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"""
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gain = random.uniform(self._min_gain_dBFS, self._max_gain_dBFS)
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audio_segment.gain_db(gain)
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