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107 lines
4.4 KiB
107 lines
4.4 KiB
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Contain the speech perturbation augmentation model."""
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import numpy as np
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from deepspeech.frontend.augmentor.base import AugmentorBase
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class SpeedPerturbAugmentor(AugmentorBase):
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"""Augmentation model for adding speed perturbation."""
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def __init__(self, rng, min_speed_rate=0.9, max_speed_rate=1.1,
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num_rates=3):
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"""speed perturbation.
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The speed perturbation in kaldi uses sox-speed instead of sox-tempo,
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and sox-speed just to resample the input,
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i.e pitch and tempo are changed both.
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"Why use speed option instead of tempo -s in SoX for speed perturbation"
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https://groups.google.com/forum/#!topic/kaldi-help/8OOG7eE4sZ8
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Sox speed:
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https://pysox.readthedocs.io/en/latest/api.html#sox.transform.Transformer
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See reference paper here:
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http://www.danielpovey.com/files/2015_interspeech_augmentation.pdf
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Espnet:
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https://espnet.github.io/espnet/_modules/espnet/transform/perturb.html
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Nemo:
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https://github.com/NVIDIA/NeMo/blob/main/nemo/collections/asr/parts/perturb.py#L92
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Args:
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rng (random.Random): Random generator object.
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min_speed_rate (float): Lower bound of new speed rate to sample and should
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not be smaller than 0.9.
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max_speed_rate (float): Upper bound of new speed rate to sample and should
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not be larger than 1.1.
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num_rates (int, optional): Number of discrete rates to allow.
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Can be a positive or negative integer. Defaults to 3.
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If a positive integer greater than 0 is provided, the range of
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speed rates will be discretized into `num_rates` values.
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If a negative integer or 0 is provided, the full range of speed rates
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will be sampled uniformly.
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Note: If a positive integer is provided and the resultant discretized
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range of rates contains the value '1.0', then those samples with rate=1.0,
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will not be augmented at all and simply skipped. This is to unnecessary
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augmentation and increase computation time. Effective augmentation chance
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in such a case is = `prob * (num_rates - 1 / num_rates) * 100`% chance
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where `prob` is the global probability of a sample being augmented.
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Raises:
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ValueError: when speed_rate error
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"""
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if min_speed_rate < 0.9:
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raise ValueError(
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"Sampling speed below 0.9 can cause unnatural effects")
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if max_speed_rate > 1.1:
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raise ValueError(
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"Sampling speed above 1.1 can cause unnatural effects")
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self._min_rate = min_speed_rate
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self._max_rate = max_speed_rate
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self._rng = rng
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self._num_rates = num_rates
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if num_rates > 0:
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self._rates = np.linspace(
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self._min_rate, self._max_rate, self._num_rates, endpoint=True)
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def __call__(self, x, uttid=None, train=True):
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if not train:
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return x
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self.transform_audio(x)
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return x
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def transform_audio(self, audio_segment):
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"""Sample a new speed rate from the given range and
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changes the speed of the given audio clip.
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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: AudioSegment|SpeechSegment
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"""
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if self._num_rates < 0:
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speed_rate = self._rng.uniform(self._min_rate, self._max_rate)
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else:
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speed_rate = self._rng.choice(self._rates)
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# Skip perturbation in case of identity speed rate
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if speed_rate == 1.0:
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return
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audio_segment.change_speed(speed_rate)
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