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50 lines
2.0 KiB
50 lines
2.0 KiB
"""Contains the noise perturb augmentation model."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from data_utils.augmentor.base import AugmentorBase
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from data_utils.utility import read_manifest
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from data_utils.audio import AudioSegment
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class NoisePerturbAugmentor(AugmentorBase):
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"""Augmentation model for adding background noise.
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:param rng: Random generator object.
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:type rng: random.Random
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:param min_snr_dB: Minimal signal noise ratio, in decibels.
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:type min_snr_dB: float
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:param max_snr_dB: Maximal signal noise ratio, in decibels.
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:type max_snr_dB: float
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:param noise_manifest_path: Manifest path for noise audio data.
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:type noise_manifest_path: basestring
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"""
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def __init__(self, rng, min_snr_dB, max_snr_dB, noise_manifest_path):
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self._min_snr_dB = min_snr_dB
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self._max_snr_dB = max_snr_dB
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self._rng = rng
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self._noise_manifest = read_manifest(manifest_path=noise_manifest_path)
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def transform_audio(self, audio_segment):
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"""Add background noise audio.
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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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noise_json = self._rng.sample(self._noise_manifest, 1)[0]
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if noise_json['duration'] < audio_segment.duration:
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raise RuntimeError("The duration of sampled noise audio is smaller "
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"than the audio segment to add effects to.")
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diff_duration = noise_json['duration'] - audio_segment.duration
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start = self._rng.uniform(0, diff_duration)
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end = start + audio_segment.duration
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noise_segment = AudioSegment.slice_from_file(
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noise_json['audio_filepath'], start=start, end=end)
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snr_dB = self._rng.uniform(self._min_snr_dB, self._max_snr_dB)
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audio_segment.add_noise(
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noise_segment, snr_dB, allow_downsampling=True, rng=self._rng)
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