Searched refs:vad_output (Results 1 – 8 of 8) sorted by relevance
| /external/webrtc/modules/audio_processing/test/py_quality_assessment/quality_assessment/ |
| D | annotations_unittest.py | 73 vad_output = e.GetVadOutput(self._VAD_TYPE_CLASS.ENERGY_THRESHOLD)
74 self.assertGreater(len(vad_output), 0)
75 self.assertGreaterEqual(float(np.sum(vad_output)) / len(vad_output),
80 vad_output = e.GetVadOutput(self._VAD_TYPE_CLASS.WEBRTC_COMMON_AUDIO)
81 self.assertGreater(len(vad_output), 0)
82 self.assertGreaterEqual(float(np.sum(vad_output)) / len(vad_output),
102 num_frames=len(vad_output),
108 plt.plot(t_vad, vad_output * np.max(level), '.')
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| D | annotations.py | 190 vad_output=self._common_audio_vad,
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| /external/rnnoise/src/ |
| D | rnn_data.c | 11027 static const DenseLayer vad_output = { variable
11050 &vad_output
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| D | rnn_reader.c | 70 ALLOC_LAYER(DenseLayer, vad_output); in rnnoise_model_from_file()
135 INPUT_DENSE(vad_output); in rnnoise_model_from_file()
166 FREE_DENSE(vad_output); in rnnoise_model_free()
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| D | rnn_data.h | 23 const DenseLayer *vad_output; member
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| D | rnn.c | 167 compute_dense(rnn->model->vad_output, vad, rnn->vad_gru_state); in compute_rnn()
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| /external/rnnoise/training/ |
| D | rnn_train.py | 66 vad_output = Dense(1, activation='sigmoid', name='vad_output', kernel_constraint=constraint, bias_c… variable
75 model = Model(inputs=main_input, outputs=[denoise_output, vad_output])
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| /external/webrtc/modules/audio_processing/agc2/rnn_vad/ |
| D | rnn.cc | 420 const auto vad_output = output_layer_.GetOutput(); in ComputeVadProbability() local
421 return vad_output[0]; in ComputeVadProbability()
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