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50 lines
1.6 KiB
50 lines
1.6 KiB
# Copyright (c) 2022 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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import unittest
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import numpy as np
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import paddle
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import paddlespeech.audio
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from .base import FeatTest
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from paddlespeech.s2t.transform.spectrogram import LogMelSpectrogram
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class TestLogMelSpectrogram(FeatTest):
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def initParmas(self):
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self.n_fft = 512
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self.hop_length = 128
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self.n_mels = 40
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def test_log_melspect(self):
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ps_melspect = LogMelSpectrogram(self.sr, self.n_mels, self.n_fft,
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self.hop_length)
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ps_res = ps_melspect(self.waveform.T).squeeze(1).T
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x = paddle.to_tensor(self.waveform)
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ps_melspect = paddlespeech.audio.features.LogMelSpectrogram(
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self.sr,
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self.n_fft,
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self.hop_length,
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power=1.0,
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n_mels=self.n_mels,
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f_min=0.0)
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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__':
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unittest.main()
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