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PaddleSpeech/deepspeech/frontend/augmentor/volume_perturb.py

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1.9 KiB

# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Contains the volume perturb augmentation model."""
from deepspeech.frontend.augmentor.base import AugmentorBase
class VolumePerturbAugmentor(AugmentorBase):
"""Augmentation model for adding random volume perturbation.
This is used for multi-loudness training of PCEN. See
https://arxiv.org/pdf/1607.05666v1.pdf
for more details.
:param rng: Random generator object.
:type rng: random.Random
:param min_gain_dBFS: Minimal gain in dBFS.
:type min_gain_dBFS: float
:param max_gain_dBFS: Maximal gain in dBFS.
:type max_gain_dBFS: float
"""
def __init__(self, rng, min_gain_dBFS, max_gain_dBFS):
self._min_gain_dBFS = min_gain_dBFS
self._max_gain_dBFS = max_gain_dBFS
self._rng = rng
def __call__(self, x, uttid=None, train=True):
if not train:
return
self.transform_audio(x)
return x
def transform_audio(self, audio_segment):
"""Change audio loadness.
Note that this is an in-place transformation.
:param audio_segment: Audio segment to add effects to.
:type audio_segment: AudioSegmenet|SpeechSegment
"""
gain = self._rng.uniform(self._min_gain_dBFS, self._max_gain_dBFS)
audio_segment.gain_db(gain)