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# Copyright (c) 2022 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. |
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# Copyright (c) 2022 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. | ||
import os | ||
import unittest | ||
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import numpy as np | ||
import paddle | ||
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from paddleaudio import load | ||
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file_dir = os.path.dirname(os.path.realpath(__file__)) | ||
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class FeatTest(unittest.TestCase): | ||
def setUp(self): | ||
self.initParmas() | ||
self.initWavInput() | ||
self.setUpDevice() | ||
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def setUpDevice(self, device='cpu'): | ||
paddle.set_device(device) | ||
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def initWavInput(self): | ||
self.waveform, self.sr = load( | ||
os.path.abspath(os.path.join(file_dir, '../wav/zh.wav'))) | ||
self.waveform = self.waveform.astype( | ||
np.float32 | ||
) # paddlespeech.s2t.transform.spectrogram only supports float32 | ||
dim = len(self.waveform.shape) | ||
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assert dim in [1, 2] | ||
if dim == 1: | ||
self.waveform = np.expand_dims(self.waveform, 0) | ||
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def initParmas(self): | ||
raise NotImplementedError |
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# Copyright (c) 2022 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. | ||
import unittest | ||
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import numpy as np | ||
import paddle | ||
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from .base import FeatTest | ||
from paddleaudio.functional.window import get_window | ||
from paddlespeech.s2t.transform.spectrogram import IStft | ||
from paddlespeech.s2t.transform.spectrogram import Stft | ||
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class ISTFT(FeatTest): | ||
def initParmas(self): | ||
self.n_fft = 512 | ||
self.hop_length = 128 | ||
self.window_str = 'hann' | ||
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def test_istft(self): | ||
ps_stft = Stft(self.n_fft, self.hop_length) | ||
ps_res = ps_stft( | ||
self.waveform.T).squeeze(1).T # (n_fft//2 + 1, n_frmaes) | ||
x = paddle.to_tensor(ps_res) | ||
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ps_istft = IStft(self.hop_length) | ||
ps_res = ps_istft(ps_res.T) | ||
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window = get_window( | ||
self.window_str, self.n_fft, dtype=self.waveform.dtype) | ||
pd_res = paddle.signal.istft( | ||
x, self.n_fft, self.hop_length, window=window) | ||
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np.testing.assert_array_almost_equal(ps_res, pd_res, decimal=5) | ||
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if __name__ == '__main__': | ||
unittest.main() |
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# Copyright (c) 2022 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. | ||
import unittest | ||
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import numpy as np | ||
import paddle | ||
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import paddleaudio | ||
from .base import FeatTest | ||
from paddlespeech.s2t.transform.spectrogram import LogMelSpectrogram | ||
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class LogMelSpect(FeatTest): | ||
def initParmas(self): | ||
self.n_fft = 512 | ||
self.hop_length = 128 | ||
self.n_mels = 40 | ||
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def test_log_melspect(self): | ||
ps_melspect = LogMelSpectrogram(self.sr, self.n_mels, self.n_fft, | ||
self.hop_length) | ||
ps_res = ps_melspect(self.waveform.T).squeeze(1).T | ||
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x = paddle.to_tensor(self.waveform) | ||
# paddlespeech.s2t的特征存在幅度谱和功率谱滥用的情况 | ||
ps_melspect = paddleaudio.features.LogMelSpectrogram( | ||
self.sr, | ||
self.n_fft, | ||
self.hop_length, | ||
power=1.0, | ||
n_mels=self.n_mels, | ||
f_min=0.0) | ||
pa_res = (ps_melspect(x) / 10.0).squeeze(0).numpy() | ||
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np.testing.assert_array_almost_equal(ps_res, pa_res, decimal=5) | ||
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if __name__ == '__main__': | ||
unittest.main() |
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# Copyright (c) 2022 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. | ||
import unittest | ||
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import numpy as np | ||
import paddle | ||
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import paddleaudio | ||
from .base import FeatTest | ||
from paddlespeech.s2t.transform.spectrogram import Spectrogram | ||
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class Spect(FeatTest): | ||
def initParmas(self): | ||
self.n_fft = 512 | ||
self.hop_length = 128 | ||
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def test_spectrogram(self): | ||
ps_spect = Spectrogram(self.n_fft, self.hop_length) | ||
ps_res = ps_spect(self.waveform.T).squeeze(1).T # Magnitude | ||
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x = paddle.to_tensor(self.waveform) | ||
pa_spect = paddleaudio.features.Spectrogram( | ||
self.n_fft, self.hop_length, power=1.0) | ||
pa_res = pa_spect(x).squeeze(0).numpy() | ||
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np.testing.assert_array_almost_equal(ps_res, pa_res, decimal=5) | ||
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if __name__ == '__main__': | ||
unittest.main() |
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# Copyright (c) 2022 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. | ||
import unittest | ||
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import numpy as np | ||
import paddle | ||
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from .base import FeatTest | ||
from paddleaudio.functional.window import get_window | ||
from paddlespeech.s2t.transform.spectrogram import Stft | ||
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class STFT(FeatTest): | ||
def initParmas(self): | ||
self.n_fft = 512 | ||
self.hop_length = 128 | ||
self.window_str = 'hann' | ||
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def test_stft(self): | ||
ps_stft = Stft(self.n_fft, self.hop_length) | ||
ps_res = ps_stft( | ||
self.waveform.T).squeeze(1).T # (n_fft//2 + 1, n_frmaes) | ||
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x = paddle.to_tensor(self.waveform) | ||
window = get_window(self.window_str, self.n_fft, dtype=x.dtype) | ||
pd_res = paddle.signal.stft( | ||
x, self.n_fft, self.hop_length, window=window).squeeze(0).numpy() | ||
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np.testing.assert_array_almost_equal(ps_res, pd_res, decimal=5) | ||
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if __name__ == '__main__': | ||
unittest.main() |
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